fix

README.md

@@ -8,6 +8,28 @@ Supported methods:
 3. P-Tuning
 4. Prompt Tuning 
 
+## Getting started
+
+```python
+from transformers import AutoModelForSeq2SeqLM
+from pet import get_pet_config,get_pet_model
+model_name_or_path = "bigscience/mt0-large"
+tokenizer_name_or_path = "bigscience/mt0-large"
+
+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)
+
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
+model = get_pet_model(model, pet_config)
+model.print_trainable_parameters()
+```
+
 ## Models support matrix
 
 ### Sequence Classification

src/pet/mapping.py

@@ -18,6 +18,7 @@ PET_TYPE_TO_CONFIG_MAPPING = {
 
 TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING = {
     "t5": ["q", "v"],
+    "mt5": ["q", "v"],
     "bart": ["q_proj", "v_proj"],
     "gpt2": ["c_attn"],
     "bloom": ["query_key_value"],