From ae609d680e967b6bc9999415a88bbd30abb2ff9a Mon Sep 17 00:00:00 2001
From: Sourab Mangrulkar <13534540+pacman100@users.noreply.github.com>
Date: Fri, 2 Dec 2022 16:21:16 +0530
Subject: [PATCH] add examples and update README

---
 Makefile                                     |    2 +-
 README.md                                    |   45 +-
 examples/pet_lora_seq2seq.ipynb              | 4815 ++++++++++++++++++
 examples/pet_lora_seq2seq_accelerate_fsdp.py |  137 +
 examples/pet_prefix_tuning_seq2seq.ipynb     | 1963 +++++++
 5 files changed, 6958 insertions(+), 4 deletions(-)
 create mode 100644 examples/pet_lora_seq2seq.ipynb
 create mode 100644 examples/pet_lora_seq2seq_accelerate_fsdp.py
 create mode 100644 examples/pet_prefix_tuning_seq2seq.ipynb

diff --git a/Makefile b/Makefile
index e1c15c5..888056d 100644
--- a/Makefile
+++ b/Makefile
@@ -1,6 +1,6 @@
 .PHONY: quality style test docs
 
-check_dirs := src
+check_dirs := src examples
 
 # Check that source code meets quality standards
 
diff --git a/README.md b/README.md
index 95eeccf..1dfafca 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,5 @@
 # 🤗 PET
-Parameter-Efficient Tuning. Intergrated with 🤗 Accelerate to scale seamlessly to large models using PyTorch FSDP. 
+Parameter-Efficient Tuning methods enable . Intergrated with 🤗 Accelerate to scale seamlessly to large models using PyTorch FSDP. 
 
 Supported methods:
 
@@ -38,19 +38,56 @@ For scaling to large models, you can leverage 🤗 Accelerate's PyTorch FSDP int
 PyTorch FSDP shards parameters, gradients and optimizer states across data parallel workers which enables
 large language models to fit on available hardware. 
 It also supports CPU offloading to further enable distributed training at scale. 
-The support for DeepSpeed ZeRO Stage-3 is currently in backlog.
 
 ```python
 from pet.utils.other import fsdp_auto_wrap_policy
 
 ...
 
-if accelerator.state.fsdp_plugin is not None:
+if os.environ.get("ACCELERATE_USE_FSDP", None) is not None:
     accelerator.state.fsdp_plugin.auto_wrap_policy = fsdp_auto_wrap_policy(model)
 
 model = accelerator.prepare(model)
 ```
 
+Example of parameter efficient tuning with `mt0-xxl` base model using 🤗 Accelerate is provided in `~examples/pet_lora_seq2seq_accelerate_fsdp.py`. 
+1. First run `accelerate config --config_file fsdp_config.yaml` and answer the questionaire. 
+Below are the contents of the config file.
+```
+command_file: null
+commands: null
+compute_environment: LOCAL_MACHINE
+deepspeed_config: {}
+distributed_type: FSDP
+downcast_bf16: 'no'
+dynamo_backend: 'NO'
+fsdp_config:
+  fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
+  fsdp_backward_prefetch_policy: BACKWARD_PRE
+  fsdp_offload_params: true
+  fsdp_sharding_strategy: 1
+  fsdp_state_dict_type: FULL_STATE_DICT
+  fsdp_transformer_layer_cls_to_wrap: T5Block
+gpu_ids: null
+machine_rank: 0
+main_process_ip: null
+main_process_port: null
+main_training_function: main
+megatron_lm_config: {}
+mixed_precision: 'no'
+num_machines: 1
+num_processes: 2
+rdzv_backend: static
+same_network: true
+tpu_name: null
+tpu_zone: null
+use_cpu: false
+```
+2. run the below command to launch example script
+```
+accelerate launch --config_file fsdp_config.yaml examples/pet_lora_seq2seq_accelerate_fsdp.py
+```
+
 
 ## Models support matrix
 
@@ -85,5 +122,7 @@ model = accelerator.prepare(model)
 
 ## Caveats:
 1. Doesn't work currently with DeeSpeed ZeRO Stage-3. Extending support with DeeSpeed ZeRO Stage-3 is in backlog.
+2. When using `P_TUNING` or `PROMPT_TUNING` with `SEQ_2_SEQ` task, remember to remove the `num_virtual_token` virtual prompt predictions from the left side of the model outputs during evaluations. 
+
 
 
diff --git a/examples/pet_lora_seq2seq.ipynb b/examples/pet_lora_seq2seq.ipynb
new file mode 100644
index 0000000..f8d86c6
--- /dev/null
+++ b/examples/pet_lora_seq2seq.ipynb
@@ -0,0 +1,4815 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "5f93b7d1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from transformers import AutoModelForSeq2SeqLM\n",
+    "from pet import get_pet_config,get_pet_model, get_pet_model_state_dict\n",
+    "import torch\n",
+    "from datasets import load_dataset\n",
+    "import os\n",
+    "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\"\n",
+    "from transformers import AutoTokenizer\n",
+    "from torch.utils.data import DataLoader\n",
+    "from transformers import default_data_collator,get_linear_schedule_with_warmup\n",
+    "from tqdm import tqdm\n",
+    "from datasets import load_dataset\n",
+    "\n",
+    "device = \"cuda\"\n",
+    "model_name_or_path = \"bigscience/mt0-large\"\n",
+    "tokenizer_name_or_path = \"bigscience/mt0-large\"\n",
+    "\n",
+    "config = {\n",
+    "    \"pet_type\":\"LORA\",\n",
+    "    \"task_type\":\"SEQ_2_SEQ_LM\",\n",
+    "    \"r\":16,\n",
+    "    \"lora_alpha\": 32,\n",
+    "    \"lora_dropout\": 0.1\n",
+    "}\n",
+    "checkpoint_name = \"financial_sentiment_analysis_lora_v1.pt\"\n",
+    "text_column = \"sentence\"\n",
+    "label_column = \"text_label\"\n",
+    "max_length=128\n",
+    "lr = 1e-3\n",
+    "num_epochs = 3\n",
+    "batch_size=8\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8d0850ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "trainable params: 4718592 || all params: 1234299904 || trainable%: 0.38228893842642636\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "PETModelForSeq2SeqLM(\n",
+       "  (base_model): LoRAModel(\n",
+       "    (model): MT5ForConditionalGeneration(\n",
+       "      (shared): Embedding(250112, 1024)\n",
+       "      (encoder): T5Stack(\n",
+       "        (embed_tokens): Embedding(250112, 1024)\n",
+       "        (block): ModuleList(\n",
+       "          (0): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (relative_attention_bias): Embedding(32, 16)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (1): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (2): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (3): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (4): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (5): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (6): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (7): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (8): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (9): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (10): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (11): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (12): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (13): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (14): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (15): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (16): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (17): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (18): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (19): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (20): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (21): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (22): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (23): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (final_layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "        (dropout): Dropout(p=0.1, inplace=False)\n",
+       "      )\n",
+       "      (decoder): T5Stack(\n",
+       "        (embed_tokens): Embedding(250112, 1024)\n",
+       "        (block): ModuleList(\n",
+       "          (0): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (relative_attention_bias): Embedding(32, 16)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (1): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (2): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (3): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (4): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (5): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (6): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (7): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (8): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (9): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (10): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (11): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (12): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (13): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (14): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (15): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (16): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (17): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (18): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (19): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (20): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (21): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (22): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "          (23): T5Block(\n",
+       "            (layer): ModuleList(\n",
+       "              (0): T5LayerSelfAttention(\n",
+       "                (SelfAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (1): T5LayerCrossAttention(\n",
+       "                (EncDecAttention): T5Attention(\n",
+       "                  (q): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                  (v): Linear(\n",
+       "                    in_features=1024, out_features=1024, bias=False\n",
+       "                    (lora_dropout): Dropout(p=0.1, inplace=False)\n",
+       "                    (lora_A): Linear(in_features=1024, out_features=16, bias=False)\n",
+       "                    (lora_B): Linear(in_features=16, out_features=1024, bias=False)\n",
+       "                  )\n",
+       "                  (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "              (2): T5LayerFF(\n",
+       "                (DenseReluDense): T5DenseGatedActDense(\n",
+       "                  (wi_0): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wi_1): Linear(in_features=1024, out_features=2816, bias=False)\n",
+       "                  (wo): Linear(in_features=2816, out_features=1024, bias=False)\n",
+       "                  (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                  (act): NewGELUActivation()\n",
+       "                )\n",
+       "                (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (final_layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "        (dropout): Dropout(p=0.1, inplace=False)\n",
+       "      )\n",
+       "      (lm_head): Linear(in_features=1024, out_features=250112, bias=False)\n",
+       "    )\n",
+       "  )\n",
+       ")"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# creating model\n",
+    "pet_config = get_pet_config(config)\n",
+    "\n",
+    "model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)\n",
+    "model = get_pet_model(model, pet_config)\n",
+    "model.print_trainable_parameters()\n",
+    "model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4ee2babf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/sourab/miniconda3/envs/ml/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:97: FutureWarning: Deprecated argument(s) used in 'dataset_info': token. Will not be supported from version '0.12'.\n",
+      "  warnings.warn(message, FutureWarning)\n",
+      "Found cached dataset financial_phrasebank (/home/sourab/.cache/huggingface/datasets/financial_phrasebank/sentences_allagree/1.0.0/550bde12e6c30e2674da973a55f57edde5181d53f5a5a34c1531c53f93b7e141)\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6de075f8208349108291ac5ab7f5c980",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4b0e67b6d93f43e4b0f6a2f8978e4b0c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/3 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a9551029c9884529bda7421a99170b51",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'sentence': 'The order was valued at USD12 .2 m.',\n",
+       " 'label': 1,\n",
+       " 'text_label': 'neutral'}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# loading dataset\n",
+    "dataset = load_dataset(\"financial_phrasebank\", 'sentences_allagree')\n",
+    "dataset = dataset[\"train\"].train_test_split(test_size=0.1)\n",
+    "dataset[\"validation\"] = dataset[\"test\"]\n",
+    "del(dataset[\"test\"])\n",
+    "\n",
+    "classes = dataset[\"train\"].features[\"label\"].names\n",
+    "dataset = dataset.map(\n",
+    "    lambda x: {\"text_label\": [classes[label] for label in x[\"label\"]]},\n",
+    "    batched=True,\n",
+    "    num_proc=1,\n",
+    "    \n",
+    ")\n",
+    "\n",
+    "dataset[\"train\"][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "adf9608c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4421971232434db1b6141e91fda2f6d7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Running tokenizer on dataset:   0%|          | 0/3 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9b2ef793d93443949f4a5d5874d4bc05",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Running tokenizer on dataset:   0%|          | 0/1 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# data preprocessing\n",
+    "tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)\n",
+    "def preprocess_function(examples):\n",
+    "    inputs = examples[text_column]\n",
+    "    targets = examples[label_column]\n",
+    "    model_inputs = tokenizer(inputs, max_length=max_length, padding=\"max_length\", truncation=True, return_tensors=\"pt\")\n",
+    "    labels = tokenizer(targets, max_length=3, padding=\"max_length\", truncation=True, return_tensors=\"pt\")\n",
+    "    labels = labels[\"input_ids\"]\n",
+    "    labels[labels==tokenizer.pad_token_id] = -100\n",
+    "    model_inputs[\"labels\"] = labels\n",
+    "    return model_inputs\n",
+    "\n",
+    "processed_datasets = dataset.map(\n",
+    "            preprocess_function,\n",
+    "            batched=True,\n",
+    "            num_proc=1,\n",
+    "            remove_columns=dataset[\"train\"].column_names,\n",
+    "            load_from_cache_file=False,\n",
+    "            desc=\"Running tokenizer on dataset\",\n",
+    "        )\n",
+    "\n",
+    "train_dataset = processed_datasets[\"train\"]\n",
+    "eval_dataset = processed_datasets[\"validation\"]\n",
+    "\n",
+    "train_dataloader = DataLoader(\n",
+    "        train_dataset, shuffle=True, collate_fn=default_data_collator, batch_size=batch_size, pin_memory=True\n",
+    "    )\n",
+    "eval_dataloader = DataLoader(eval_dataset, collate_fn=default_data_collator, batch_size=batch_size, pin_memory=True)\n",
+    "\n",
+    "\n",
+    "\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "f733a3c6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# optimizer and lr scheduler\n",
+    "optimizer = torch.optim.AdamW(model.parameters(), lr=lr)\n",
+    "lr_scheduler = get_linear_schedule_with_warmup(\n",
+    "    optimizer=optimizer,\n",
+    "    num_warmup_steps=0,\n",
+    "    num_training_steps=(len(train_dataloader) * num_epochs),\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "6b3a4090",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:53<00:00,  4.80it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:02<00:00, 14.16it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=0: train_ppl=tensor(13.6966, device='cuda:0') train_epoch_loss=tensor(2.6171, device='cuda:0') eval_ppl=tensor(1.0046, device='cuda:0') eval_epoch_loss=tensor(0.0046, device='cuda:0')\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:52<00:00,  4.88it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:02<00:00, 14.20it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=1: train_ppl=tensor(1.5893, device='cuda:0') train_epoch_loss=tensor(0.4633, device='cuda:0') eval_ppl=tensor(1.0020, device='cuda:0') eval_epoch_loss=tensor(0.0020, device='cuda:0')\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:52<00:00,  4.87it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:02<00:00, 14.18it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=2: train_ppl=tensor(1.3210, device='cuda:0') train_epoch_loss=tensor(0.2784, device='cuda:0') eval_ppl=tensor(1.0026, device='cuda:0') eval_epoch_loss=tensor(0.0026, device='cuda:0')\n"
+     ]
+    }
+   ],
+   "source": [
+    "# training and evaluation\n",
+    "model = model.to(device)\n",
+    "\n",
+    "for epoch in range(num_epochs):\n",
+    "    model.train()\n",
+    "    total_loss = 0\n",
+    "    for step, batch in enumerate(tqdm(train_dataloader)):\n",
+    "        batch = {k: v.to(device) for k, v in batch.items()}\n",
+    "        outputs = model(**batch)\n",
+    "        loss = outputs.loss\n",
+    "        total_loss += loss.detach().float()\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "        lr_scheduler.step()\n",
+    "        optimizer.zero_grad()\n",
+    "\n",
+    "    model.eval()\n",
+    "    eval_loss = 0\n",
+    "    eval_preds = []\n",
+    "    for step, batch in enumerate(tqdm(eval_dataloader)):\n",
+    "        batch = {k: v.to(device) for k, v in batch.items()}\n",
+    "        with torch.no_grad():\n",
+    "            outputs = model(**batch)\n",
+    "        loss = outputs.loss\n",
+    "        eval_loss += loss.detach().float()\n",
+    "        eval_preds.extend(tokenizer.batch_decode(torch.argmax(outputs.logits, -1).detach().cpu().numpy(), skip_special_tokens=True))\n",
+    "\n",
+    "    eval_epoch_loss = eval_loss/len(train_dataloader)\n",
+    "    eval_ppl = torch.exp(eval_epoch_loss)\n",
+    "    train_epoch_loss = total_loss/len(eval_dataloader)\n",
+    "    train_ppl = torch.exp(train_epoch_loss)\n",
+    "    print(f\"{epoch=}: {train_ppl=} {train_epoch_loss=} {eval_ppl=} {eval_epoch_loss=}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "6cafa67b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "accuracy=98.23788546255507 % on the evaluation dataset\n",
+      "eval_preds[:10]=['neutral', 'neutral', 'positive', 'positive', 'neutral', 'neutral', 'neutral', 'neutral', 'neutral', 'neutral']\n",
+      "dataset['validation']['text_label'][:10]=['neutral', 'neutral', 'positive', 'positive', 'neutral', 'neutral', 'neutral', 'neutral', 'neutral', 'neutral']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# print accuracy\n",
+    "correct =0\n",
+    "total = 0\n",
+    "for pred,true in zip(eval_preds, dataset[\"validation\"][\"text_label\"]):\n",
+    "    if pred.strip()==true.strip():\n",
+    "        correct+=1\n",
+    "    total+=1  \n",
+    "accuracy = correct/total*100\n",
+    "print(f\"{accuracy=} % on the evaluation dataset\")\n",
+    "print(f\"{eval_preds[:10]=}\")\n",
+    "print(f\"{dataset['validation']['text_label'][:10]=}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a8de6005",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'base_model.model.encoder.block.0.layer.0.SelfAttention.q.lora_A.weight': tensor([[ 0.0011,  0.0126, -0.0392,  ...,  0.0117, -0.0080,  0.0227],\n",
+      "        [ 0.0239, -0.0152,  0.0174,  ..., -0.0209, -0.0093, -0.0250],\n",
+      "        [ 0.0197,  0.0023,  0.0045,  ..., -0.0073, -0.0106, -0.0038],\n",
+      "        ...,\n",
+      "        [-0.0116,  0.0015,  0.0146,  ...,  0.0017, -0.0237, -0.0077],\n",
+      "        [ 0.0143,  0.0330,  0.0059,  ...,  0.0124,  0.0045, -0.0180],\n",
+      "        [ 0.0095,  0.0024,  0.0352,  ...,  0.0064,  0.0230, -0.0452]],\n",
+      "       device='cuda:0'), 'base_model.model.encoder.block.0.layer.0.SelfAttention.q.lora_B.weight': tensor([[ 0.0161, -0.0037,  0.0014,  ...,  0.0039,  0.0235, -0.0148],\n",
+      "        [-0.0086, -0.0180,  0.0253,  ...,  0.0277,  0.0029, -0.0193],\n",
+      "        [ 0.0004,  0.0172,  0.0078,  ...,  0.0094, -0.0130,  0.0012],\n",
+      "        ...,\n",
+      "        [ 0.0010,  0.0024,  0.0202,  ...,  0.0259, -0.0117,  0.0107],\n",
+      "        [ 0.0256,  0.0210, -0.0293,  ..., -0.0210,  0.0059, -0.0250],\n",
+      "        [-0.0056, -0.0048,  0.0187,  ...,  0.0086, -0.0178,  0.0021]],\n",
+      "       device='cuda:0'), 'base_model.model.encoder.block.0.layer.0.SelfAttention.v.lora_A.weight': tensor([[ 0.0205, -0.0127,  0.0213,  ..., -0.0042,  0.0034,  0.0243],\n",
+      "        [ 0.0197, -0.0426, -0.0326,  ...,  0.0069, -0.0203,  0.0358],\n",
+      "        [-0.0216,  0.0100, -0.0084,  ...,  0.0446, -0.0540,  0.0452],\n",
+      "        ...,\n",
+      "        [ 0.0578, -0.0072,  0.0047,  ..., -0.0078, -0.0231,  0.0116],\n",
+      "        [ 0.0131,  0.0072,  0.0372,  ..., -0.0183, -0.0214, -0.0139],\n",
+      "        [ 0.0013,  0.0402, -0.0062,  ...,  0.0365,  0.0286, -0.0329]],\n",
+      "       device='cuda:0'), 'base_model.model.encoder.block.0.layer.0.SelfAttention.v.lora_B.weight': tensor([[ 0.0046, -0.0044,  0.0061,  ..., -0.0013, -0.0303, -0.0034],\n",
+      "        [ 0.0060,  0.0068, -0.0019,  ..., -0.0046, -0.0336, -0.0189],\n",
+      "        [-0.0039, -0.0053,  0.0089,  ..., -0.0128,  0.0059, -0.0216],\n",
+      "        ...,\n",
+      "        [ 0.0052, -0.0199, -0.0261,  ..., -0.0253,  0.0173, -0.0027],\n",
+      "        [ 0.0098, -0.0081, -0.0105,  ..., -0.0074, -0.0016, -0.0026],\n",
+      "        [ 0.0134, -0.0060,  0.0122,  ...,  0.0021, -0.0014,  0.0148]],\n",
+      "       device='cuda:0'), 'base_model.model.encoder.block.1.layer.0.SelfAttention.q.lora_A.weight': tensor([[-0.0306, -0.0243, -0.0414,  ...,  0.0121,  0.0280,  0.0006],\n",
+      "        [-0.0425, -0.0292,  0.0076,  ...,  0.0322, -0.0244,  0.0346],\n",
+      "        [-0.0081,  0.0155, -0.0289,  ..., -0.0078,  0.0121, -0.0135],\n",
+      "        ...,\n",
+      "        [ 0.0161,  0.0303, -0.0498,  ..., -0.0148,  0.0022, -0.0115],\n",
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+      "        [-0.0075, -0.0570, -0.0182,  ...,  0.0037,  0.0248, -0.0176]],\n",
+      "       device='cuda:0'), 'base_model.model.decoder.block.21.layer.1.EncDecAttention.q.lora_B.weight': tensor([[-0.0168,  0.0255,  0.0151,  ..., -0.0183, -0.0177, -0.0194],\n",
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+      "          1.2606e-02,  4.8337e-02],\n",
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+      "          9.3858e-03, -3.2569e-02]], device='cuda:0'), 'base_model.model.decoder.block.21.layer.1.EncDecAttention.v.lora_B.weight': tensor([[ 0.0311, -0.0313, -0.0311,  ..., -0.0332,  0.0247, -0.0304],\n",
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+      "       device='cuda:0'), 'base_model.model.decoder.block.22.layer.1.EncDecAttention.q.lora_B.weight': tensor([[ 0.0172,  0.0150, -0.0139,  ..., -0.0159, -0.0151, -0.0160],\n",
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+      "       device='cuda:0'), 'base_model.model.decoder.block.22.layer.1.EncDecAttention.v.lora_A.weight': tensor([[ 0.0323,  0.0615, -0.0286,  ..., -0.0212,  0.0202,  0.0314],\n",
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+      "       device='cuda:0'), 'base_model.model.decoder.block.22.layer.1.EncDecAttention.v.lora_B.weight': tensor([[ 0.0026,  0.0069,  0.0095,  ..., -0.0012, -0.0045, -0.0018],\n",
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+      "       device='cuda:0'), 'base_model.model.decoder.block.23.layer.0.SelfAttention.q.lora_A.weight': tensor([[ 0.0229,  0.0198, -0.0208,  ..., -0.0067,  0.0257, -0.0064],\n",
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+      "       device='cuda:0'), 'base_model.model.decoder.block.23.layer.0.SelfAttention.q.lora_B.weight': tensor([[-9.2302e-03,  4.7082e-04, -1.6876e-03,  ...,  1.5358e-03,\n",
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+      "         -1.1545e-02,  7.7533e-03]], device='cuda:0'), 'base_model.model.decoder.block.23.layer.0.SelfAttention.v.lora_A.weight': tensor([[-0.0188,  0.0154,  0.0271,  ..., -0.0192,  0.0154,  0.0396],\n",
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+      "        [-0.0486,  0.0265,  0.0539,  ..., -0.0064,  0.0338,  0.0425]],\n",
+      "       device='cuda:0'), 'base_model.model.decoder.block.23.layer.0.SelfAttention.v.lora_B.weight': tensor([[ 0.0036, -0.0072,  0.0104,  ...,  0.0092,  0.0054,  0.0088],\n",
+      "        [ 0.0053, -0.0083,  0.0139,  ...,  0.0087,  0.0064,  0.0107],\n",
+      "        [-0.0054,  0.0058, -0.0056,  ..., -0.0039, -0.0077, -0.0046],\n",
+      "        ...,\n",
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+      "        [ 0.0070, -0.0056, -0.0022,  ...,  0.0054,  0.0060, -0.0005]],\n",
+      "       device='cuda:0'), 'base_model.model.decoder.block.23.layer.1.EncDecAttention.q.lora_A.weight': tensor([[ 0.0013, -0.0205, -0.0237,  ..., -0.0034,  0.0223, -0.0525],\n",
+      "        [-0.0195, -0.0254, -0.0189,  ...,  0.0134,  0.0543, -0.0611],\n",
+      "        [ 0.0078,  0.0246, -0.0145,  ...,  0.0244,  0.0562, -0.0179],\n",
+      "        ...,\n",
+      "        [-0.0164, -0.0022, -0.0291,  ..., -0.0274, -0.0185, -0.0195],\n",
+      "        [ 0.0101,  0.0265,  0.0126,  ...,  0.0248,  0.0240, -0.0185],\n",
+      "        [-0.0226, -0.0008, -0.0094,  ...,  0.0020, -0.0359, -0.0004]],\n",
+      "       device='cuda:0'), 'base_model.model.decoder.block.23.layer.1.EncDecAttention.q.lora_B.weight': tensor([[-1.3781e-02, -1.4603e-02, -1.4217e-02,  ..., -9.6741e-03,\n",
+      "         -1.7460e-02,  1.1197e-02],\n",
+      "        [ 2.7672e-03,  5.4598e-03, -8.9388e-05,  ...,  2.6880e-03,\n",
+      "          1.1293e-02, -9.0429e-03],\n",
+      "        [ 3.1708e-03, -5.6693e-04, -4.4513e-03,  ...,  1.0293e-03,\n",
+      "          1.9967e-03, -4.6050e-03],\n",
+      "        ...,\n",
+      "        [-1.9154e-02,  2.7257e-03, -2.3589e-03,  ...,  1.8899e-03,\n",
+      "          6.3871e-03, -4.6289e-03],\n",
+      "        [ 1.3242e-03,  1.7306e-03, -3.5451e-03,  ..., -3.5201e-03,\n",
+      "         -5.5426e-03,  4.4722e-03],\n",
+      "        [ 1.3347e-02, -6.4381e-03, -1.2333e-02,  ..., -5.1522e-03,\n",
+      "         -1.4272e-02,  1.4489e-02]], device='cuda:0'), 'base_model.model.decoder.block.23.layer.1.EncDecAttention.v.lora_A.weight': tensor([[-0.0109, -0.0416,  0.0268,  ...,  0.0437, -0.0096, -0.0408],\n",
+      "        [-0.0006, -0.0368, -0.0175,  ...,  0.0711, -0.0297, -0.0360],\n",
+      "        [-0.0097, -0.0302, -0.0101,  ...,  0.0609, -0.0160, -0.0315],\n",
+      "        ...,\n",
+      "        [-0.0348,  0.0250,  0.0112,  ..., -0.0480,  0.0094,  0.0005],\n",
+      "        [-0.0217, -0.0358, -0.0137,  ...,  0.0188, -0.0225, -0.0686],\n",
+      "        [-0.0249, -0.0334, -0.0092,  ...,  0.0849, -0.0285, -0.0345]],\n",
+      "       device='cuda:0'), 'base_model.model.decoder.block.23.layer.1.EncDecAttention.v.lora_B.weight': tensor([[-0.0244, -0.0160, -0.0185,  ..., -0.0134, -0.0150, -0.0029],\n",
+      "        [-0.0028,  0.0118,  0.0127,  ...,  0.0023,  0.0139,  0.0067],\n",
+      "        [ 0.0218,  0.0264,  0.0261,  ...,  0.0093,  0.0255,  0.0199],\n",
+      "        ...,\n",
+      "        [-0.0049, -0.0083, -0.0071,  ..., -0.0327, -0.0097,  0.0223],\n",
+      "        [ 0.0283,  0.0257,  0.0250,  ...,  0.0135,  0.0239, -0.0075],\n",
+      "        [ 0.0004, -0.0003, -0.0002,  ..., -0.0289, -0.0049,  0.0312]],\n",
+      "       device='cuda:0')}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# saving model\n",
+    "state_dict = get_pet_model_state_dict(model)\n",
+    "torch.save(state_dict, checkpoint_name)\n",
+    "print(state_dict)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "bd20cd4c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "19M\tfinancial_sentiment_analysis_lora_v1.pt\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!du -h $checkpoint_name"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "76c2fc29",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.10.5 64-bit",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.5"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/pet_lora_seq2seq_accelerate_fsdp.py b/examples/pet_lora_seq2seq_accelerate_fsdp.py
new file mode 100644
index 0000000..5e0940f
--- /dev/null
+++ b/examples/pet_lora_seq2seq_accelerate_fsdp.py
@@ -0,0 +1,137 @@
+import torch
+from accelerate import Accelerator
+from torch.utils.data import DataLoader
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, default_data_collator, get_linear_schedule_with_warmup
+
+from datasets import load_dataset
+from pet import get_pet_config, get_pet_model, get_pet_model_state_dict
+from pet.utils.other import fsdp_auto_wrap_policy
+from tqdm import tqdm
+
+
+def main():
+    accelerator = Accelerator()
+    model_name_or_path = "bigscience/mt0-xxl"
+    batch_size = 16
+    text_column = "sentence"
+    label_column = "text_label"
+    max_length = 64
+    lr = 1e-3
+    num_epochs = 1
+
+    config = {"pet_type": "LORA", "task_type": "SEQ_2_SEQ_LM", "r": 8, "lora_alpha": 32, "lora_dropout": 0.1}
+    pet_config = get_pet_config(config)
+    checkpoint_name = "financial_sentiment_analysis_lora_fsdp_v1.pt"
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+    model = get_pet_model(model, pet_config)
+    accelerator.print(model.print_trainable_parameters())
+
+    dataset = load_dataset("financial_phrasebank", "sentences_allagree")
+    dataset = dataset["train"].train_test_split(test_size=0.1)
+    dataset["validation"] = dataset["test"]
+    del dataset["test"]
+
+    classes = dataset["train"].features["label"].names
+    dataset = dataset.map(
+        lambda x: {"text_label": [classes[label] for label in x["label"]]},
+        batched=True,
+        num_proc=1,
+    )
+
+    tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
+
+    def preprocess_function(examples):
+        inputs = examples[text_column]
+        targets = examples[label_column]
+        model_inputs = tokenizer(
+            inputs, max_length=max_length, padding="max_length", truncation=True, return_tensors="pt"
+        )
+        labels = tokenizer(targets, max_length=3, padding="max_length", truncation=True, return_tensors="pt")
+        labels = labels["input_ids"]
+        labels[labels == tokenizer.pad_token_id] = -100
+        model_inputs["labels"] = labels
+        return model_inputs
+
+    processed_datasets = dataset.map(
+        preprocess_function,
+        batched=True,
+        num_proc=1,
+        remove_columns=dataset["train"].column_names,
+        load_from_cache_file=False,
+        desc="Running tokenizer on dataset",
+    )
+
+    train_dataset = processed_datasets["train"]
+    eval_dataset = processed_datasets["validation"]
+
+    train_dataloader = DataLoader(
+        train_dataset, shuffle=True, collate_fn=default_data_collator, batch_size=batch_size, pin_memory=True
+    )
+    eval_dataloader = DataLoader(
+        eval_dataset, collate_fn=default_data_collator, batch_size=batch_size, pin_memory=True
+    )
+
+    optimizer = torch.optim.AdamW(model.parameters(), lr=lr)
+    lr_scheduler = get_linear_schedule_with_warmup(
+        optimizer=optimizer,
+        num_warmup_steps=0,
+        num_training_steps=(len(train_dataloader) * num_epochs),
+    )
+
+    if accelerator.state.fsdp_plugin is not None:
+        accelerator.state.fsdp_plugin.auto_wrap_policy = fsdp_auto_wrap_policy(model)
+
+    model, train_dataloader, eval_dataloader, optimizer, lr_scheduler = accelerator.prepare(
+        model, train_dataloader, eval_dataloader, optimizer, lr_scheduler
+    )
+    accelerator.print(model)
+
+    for epoch in range(num_epochs):
+        model.train()
+        total_loss = 0
+        for step, batch in enumerate(tqdm(train_dataloader)):
+            outputs = model(**batch)
+            loss = outputs.loss
+            total_loss += loss.detach().float()
+            loss.backward()
+            optimizer.step()
+            lr_scheduler.step()
+            optimizer.zero_grad()
+
+        model.eval()
+        eval_loss = 0
+        eval_preds = []
+        for step, batch in enumerate(tqdm(eval_dataloader)):
+            with torch.no_grad():
+                outputs = model(**batch)
+            loss = outputs.loss
+            eval_loss += loss.detach().float()
+            eval_preds.extend(
+                tokenizer.batch_decode(
+                    accelerator.gather_for_metrics(torch.argmax(outputs.logits, -1)).detach().cpu().numpy(),
+                    skip_special_tokens=True,
+                )
+            )
+
+        eval_epoch_loss = eval_loss / len(train_dataloader)
+        eval_ppl = torch.exp(eval_epoch_loss)
+        train_epoch_loss = total_loss / len(eval_dataloader)
+        train_ppl = torch.exp(train_epoch_loss)
+        accelerator.print(f"{epoch=}: {train_ppl=} {train_epoch_loss=} {eval_ppl=} {eval_epoch_loss=}")
+
+        correct = 0
+        total = 0
+        for pred, true in zip(eval_preds, dataset["validation"][label_column]):
+            if pred.strip() == true.strip():
+                correct += 1
+            total += 1
+        accuracy = correct / total * 100
+        accelerator.print(f"{accuracy=}")
+        accelerator.print(f"{eval_preds[:10]=}")
+        accelerator.wait_for_everyone()
+        accelerator.save(get_pet_model_state_dict(model), checkpoint_name)
+        accelerator.wait_for_everyone()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/examples/pet_prefix_tuning_seq2seq.ipynb b/examples/pet_prefix_tuning_seq2seq.ipynb
new file mode 100644
index 0000000..a1d5dc4
--- /dev/null
+++ b/examples/pet_prefix_tuning_seq2seq.ipynb
@@ -0,0 +1,1963 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5f93b7d1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from transformers import AutoModelForSeq2SeqLM\n",
+    "from pet import get_pet_config,get_pet_model, get_pet_model_state_dict\n",
+    "import torch\n",
+    "from datasets import load_dataset\n",
+    "import os\n",
+    "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\"\n",
+    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"3\"\n",
+    "from transformers import AutoTokenizer\n",
+    "from torch.utils.data import DataLoader\n",
+    "from transformers import default_data_collator,get_linear_schedule_with_warmup\n",
+    "from tqdm import tqdm\n",
+    "from datasets import load_dataset\n",
+    "\n",
+    "device = \"cuda\"\n",
+    "model_name_or_path = \"t5-large\"\n",
+    "tokenizer_name_or_path = \"t5-large\"\n",
+    "\n",
+    "config = {\n",
+    "    \"pet_type\":\"PREFIX_TUNING\",\n",
+    "    \"task_type\":\"SEQ_2_SEQ_LM\",\n",
+    "    \"num_virtual_tokens\": 20\n",
+    "}\n",
+    "checkpoint_name = \"financial_sentiment_analysis_prefix_tuning_v1.pt\"\n",
+    "text_column = \"sentence\"\n",
+    "label_column = \"text_label\"\n",
+    "max_length=128\n",
+    "lr = 1e-2\n",
+    "num_epochs = 5\n",
+    "batch_size=8\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8d0850ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3d73e8a9f76d4a2e918238f8ad0b2a30",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading:   0%|          | 0.00/1.20k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2965839a8e7f48fdafe2d7a909666b25",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading:   0%|          | 0.00/2.95G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "trainable params: 983040 || all params: 738651136 || trainable%: 0.13308583065659835\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "PETModelForSeq2SeqLM(\n",
+       "  (base_model): T5ForConditionalGeneration(\n",
+       "    (shared): Embedding(32128, 1024)\n",
+       "    (encoder): T5Stack(\n",
+       "      (embed_tokens): Embedding(32128, 1024)\n",
+       "      (block): ModuleList(\n",
+       "        (0): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (relative_attention_bias): Embedding(32, 16)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (1): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (2): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (3): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (4): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (5): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (6): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (7): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (8): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (9): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (10): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (11): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (12): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (13): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (14): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (15): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (16): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (17): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (18): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (19): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (20): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (21): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (22): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (23): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "      )\n",
+       "      (final_layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "      (dropout): Dropout(p=0.1, inplace=False)\n",
+       "    )\n",
+       "    (decoder): T5Stack(\n",
+       "      (embed_tokens): Embedding(32128, 1024)\n",
+       "      (block): ModuleList(\n",
+       "        (0): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (relative_attention_bias): Embedding(32, 16)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (1): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (2): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (3): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (4): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (5): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (6): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (7): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (8): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (9): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (10): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (11): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (12): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (13): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (14): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (15): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (16): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (17): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (18): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (19): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (20): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (21): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (22): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (23): T5Block(\n",
+       "          (layer): ModuleList(\n",
+       "            (0): T5LayerSelfAttention(\n",
+       "              (SelfAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (1): T5LayerCrossAttention(\n",
+       "              (EncDecAttention): T5Attention(\n",
+       "                (q): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (k): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (v): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "                (o): Linear(in_features=1024, out_features=1024, bias=False)\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "            (2): T5LayerFF(\n",
+       "              (DenseReluDense): T5DenseActDense(\n",
+       "                (wi): Linear(in_features=1024, out_features=4096, bias=False)\n",
+       "                (wo): Linear(in_features=4096, out_features=1024, bias=False)\n",
+       "                (dropout): Dropout(p=0.1, inplace=False)\n",
+       "                (act): ReLU()\n",
+       "              )\n",
+       "              (layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "              (dropout): Dropout(p=0.1, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "      )\n",
+       "      (final_layer_norm): FusedRMSNorm(torch.Size([1024]), eps=1e-06, elementwise_affine=True)\n",
+       "      (dropout): Dropout(p=0.1, inplace=False)\n",
+       "    )\n",
+       "    (lm_head): Linear(in_features=1024, out_features=32128, bias=False)\n",
+       "  )\n",
+       "  (word_embeddings): Embedding(32128, 1024)\n",
+       "  (prompt_encoder): PrefixEncoder(\n",
+       "    (embedding): Embedding(20, 49152)\n",
+       "  )\n",
+       ")"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# creating model\n",
+    "pet_config = get_pet_config(config)\n",
+    "\n",
+    "model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)\n",
+    "model = get_pet_model(model, pet_config)\n",
+    "model.print_trainable_parameters()\n",
+    "model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "4ee2babf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/sourab/miniconda3/envs/ml/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:97: FutureWarning: Deprecated argument(s) used in 'dataset_info': token. Will not be supported from version '0.12'.\n",
+      "  warnings.warn(message, FutureWarning)\n",
+      "Found cached dataset financial_phrasebank (/home/sourab/.cache/huggingface/datasets/financial_phrasebank/sentences_allagree/1.0.0/550bde12e6c30e2674da973a55f57edde5181d53f5a5a34c1531c53f93b7e141)\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e3f8b8faca0a4112b2c3499faee9544b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "935c8aebde284a5784348588e0bb013a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/3 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e3487cd55f6847588492bf7fa51348ca",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'sentence': 'ADPnews - Feb 5 , 2010 - Finnish real estate investor Sponda Oyj HEL : SDA1V said today that it slipped to a net loss of EUR 81.5 million USD 11.8 m in 2009 from a profit of EUR 29.3 million in 2008 .',\n",
+       " 'label': 0,\n",
+       " 'text_label': 'negative'}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# loading dataset\n",
+    "dataset = load_dataset(\"financial_phrasebank\", 'sentences_allagree')\n",
+    "dataset = dataset[\"train\"].train_test_split(test_size=0.1)\n",
+    "dataset[\"validation\"] = dataset[\"test\"]\n",
+    "del(dataset[\"test\"])\n",
+    "\n",
+    "classes = dataset[\"train\"].features[\"label\"].names\n",
+    "dataset = dataset.map(\n",
+    "    lambda x: {\"text_label\": [classes[label] for label in x[\"label\"]]},\n",
+    "    batched=True,\n",
+    "    num_proc=1,\n",
+    "    \n",
+    ")\n",
+    "\n",
+    "dataset[\"train\"][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "adf9608c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2ce088f4437d4e2c80c267332a5b84e5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading:   0%|          | 0.00/792k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4e5f69b61f194220b39336e48edd2f9e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading:   0%|          | 0.00/1.39M [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/sourab/transformers/src/transformers/models/t5/tokenization_t5_fast.py:156: FutureWarning: This tokenizer was incorrectly instantiated with a model max length of 512 which will be corrected in Transformers v5.\n",
+      "For now, this behavior is kept to avoid breaking backwards compatibility when padding/encoding with `truncation is True`.\n",
+      "- Be aware that you SHOULD NOT rely on t5-large automatically truncating your input to 512 when padding/encoding.\n",
+      "- If you want to encode/pad to sequences longer than 512 you can either instantiate this tokenizer with `model_max_length` or pass `max_length` when encoding/padding.\n",
+      "- To avoid this warning, please instantiate this tokenizer with `model_max_length` set to your preferred value.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "230c5631891e4ea8ac7a1b39f315a4f0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Running tokenizer on dataset:   0%|          | 0/3 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b581e5677d2a45459ceb725534ed0891",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Running tokenizer on dataset:   0%|          | 0/1 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# data preprocessing\n",
+    "tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)\n",
+    "def preprocess_function(examples):\n",
+    "    inputs = examples[text_column]\n",
+    "    targets = examples[label_column]\n",
+    "    model_inputs = tokenizer(inputs, max_length=max_length, padding=\"max_length\", truncation=True, return_tensors=\"pt\")\n",
+    "    labels = tokenizer(targets, max_length=2, padding=\"max_length\", truncation=True, return_tensors=\"pt\")\n",
+    "    labels = labels[\"input_ids\"]\n",
+    "    labels[labels==tokenizer.pad_token_id] = -100\n",
+    "    model_inputs[\"labels\"] = labels\n",
+    "    return model_inputs\n",
+    "\n",
+    "processed_datasets = dataset.map(\n",
+    "            preprocess_function,\n",
+    "            batched=True,\n",
+    "            num_proc=1,\n",
+    "            remove_columns=dataset[\"train\"].column_names,\n",
+    "            load_from_cache_file=False,\n",
+    "            desc=\"Running tokenizer on dataset\",\n",
+    "        )\n",
+    "\n",
+    "train_dataset = processed_datasets[\"train\"]\n",
+    "eval_dataset = processed_datasets[\"validation\"]\n",
+    "\n",
+    "train_dataloader = DataLoader(\n",
+    "        train_dataset, shuffle=True, collate_fn=default_data_collator, batch_size=batch_size, pin_memory=True\n",
+    "    )\n",
+    "eval_dataloader = DataLoader(eval_dataset, collate_fn=default_data_collator, batch_size=batch_size, pin_memory=True)\n",
+    "\n",
+    "\n",
+    "\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "f733a3c6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# optimizer and lr scheduler\n",
+    "optimizer = torch.optim.AdamW(model.parameters(), lr=lr)\n",
+    "lr_scheduler = get_linear_schedule_with_warmup(\n",
+    "    optimizer=optimizer,\n",
+    "    num_warmup_steps=0,\n",
+    "    num_training_steps=(len(train_dataloader) * num_epochs),\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "6b3a4090",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:20<00:00, 12.27it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:01<00:00, 17.32it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=0: train_ppl=tensor(2697769., device='cuda:0') train_epoch_loss=tensor(14.8079, device='cuda:0') eval_ppl=tensor(1.0089, device='cuda:0') eval_epoch_loss=tensor(0.0089, device='cuda:0')\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:19<00:00, 12.75it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:01<00:00, 17.33it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=1: train_ppl=tensor(2.9475, device='cuda:0') train_epoch_loss=tensor(1.0809, device='cuda:0') eval_ppl=tensor(1.0072, device='cuda:0') eval_epoch_loss=tensor(0.0072, device='cuda:0')\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:20<00:00, 12.71it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:01<00:00, 17.31it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=2: train_ppl=tensor(2.0588, device='cuda:0') train_epoch_loss=tensor(0.7221, device='cuda:0') eval_ppl=tensor(1.0055, device='cuda:0') eval_epoch_loss=tensor(0.0054, device='cuda:0')\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:20<00:00, 12.70it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:01<00:00, 17.32it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=3: train_ppl=tensor(1.7939, device='cuda:0') train_epoch_loss=tensor(0.5844, device='cuda:0') eval_ppl=tensor(1.0063, device='cuda:0') eval_epoch_loss=tensor(0.0063, device='cuda:0')\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████| 255/255 [00:19<00:00, 13.01it/s]\n",
+      "100%|███████████████████████████████████████████████████████████████| 29/29 [00:01<00:00, 17.33it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "epoch=4: train_ppl=tensor(1.7740, device='cuda:0') train_epoch_loss=tensor(0.5732, device='cuda:0') eval_ppl=tensor(1.0062, device='cuda:0') eval_epoch_loss=tensor(0.0061, device='cuda:0')\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# training and evaluation\n",
+    "model = model.to(device)\n",
+    "\n",
+    "for epoch in range(num_epochs):\n",
+    "    model.train()\n",
+    "    total_loss = 0\n",
+    "    for step, batch in enumerate(tqdm(train_dataloader)):\n",
+    "        batch = {k: v.to(device) for k, v in batch.items()}\n",
+    "        outputs = model(**batch)\n",
+    "        loss = outputs.loss\n",
+    "        total_loss += loss.detach().float()\n",
+    "        loss.backward()\n",
+    "        optimizer.step()\n",
+    "        lr_scheduler.step()\n",
+    "        optimizer.zero_grad()\n",
+    "\n",
+    "    model.eval()\n",
+    "    eval_loss = 0\n",
+    "    eval_preds = []\n",
+    "    for step, batch in enumerate(tqdm(eval_dataloader)):\n",
+    "        batch = {k: v.to(device) for k, v in batch.items()}\n",
+    "        with torch.no_grad():\n",
+    "            outputs = model(**batch)\n",
+    "        loss = outputs.loss\n",
+    "        eval_loss += loss.detach().float()\n",
+    "        eval_preds.extend(tokenizer.batch_decode(torch.argmax(outputs.logits, -1).detach().cpu().numpy(), skip_special_tokens=True))\n",
+    "\n",
+    "    eval_epoch_loss = eval_loss/len(train_dataloader)\n",
+    "    eval_ppl = torch.exp(eval_epoch_loss)\n",
+    "    train_epoch_loss = total_loss/len(eval_dataloader)\n",
+    "    train_ppl = torch.exp(train_epoch_loss)\n",
+    "    print(f\"{epoch=}: {train_ppl=} {train_epoch_loss=} {eval_ppl=} {eval_epoch_loss=}\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "6cafa67b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "accuracy=96.47577092511013 % on the evaluation dataset\n",
+      "eval_preds[:10]=['neutral', 'neutral', 'neutral', 'negative', 'neutral', 'neutral', 'neutral', 'neutral', 'positive', 'positive']\n",
+      "dataset['validation']['text_label'][:10]=['neutral', 'neutral', 'neutral', 'negative', 'neutral', 'neutral', 'neutral', 'neutral', 'positive', 'positive']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# print accuracy\n",
+    "correct =0\n",
+    "total = 0\n",
+    "for pred,true in zip(eval_preds, dataset[\"validation\"][\"text_label\"]):\n",
+    "    if pred.strip()==true.strip():\n",
+    "        correct+=1\n",
+    "    total+=1  \n",
+    "accuracy = correct/total*100\n",
+    "print(f\"{accuracy=} % on the evaluation dataset\")\n",
+    "print(f\"{eval_preds[:10]=}\")\n",
+    "print(f\"{dataset['validation']['text_label'][:10]=}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a8de6005",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'prompt_embeddings': tensor([[-0.3165, -0.8389,  0.3262,  ..., -1.5049, -1.6963,  0.3444],\n",
+      "        [-1.8359,  1.1936,  1.0483,  ...,  0.6197, -0.4452,  0.5844],\n",
+      "        [-0.6027,  0.3246, -1.5601,  ..., -0.3645,  0.2329,  0.3402],\n",
+      "        ...,\n",
+      "        [-1.9525, -0.5035,  0.8474,  ...,  0.4793, -0.0789, -0.9305],\n",
+      "        [-1.9741,  0.5242, -2.0594,  ..., -0.7970, -0.4889,  2.7323],\n",
+      "        [ 0.9355, -0.2714,  0.4610,  ...,  0.2692, -1.5801, -1.6405]])}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# saving model\n",
+    "state_dict = get_pet_model_state_dict(model)\n",
+    "torch.save(state_dict, checkpoint_name)\n",
+    "print(state_dict)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "bd20cd4c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3,8M\tfinancial_sentiment_analysis_prefix_tuning_v1.pt\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!du -h $checkpoint_name"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "76c2fc29",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}