From 122f708ae8551f5b88cfbe3b9579fcdb3cb1f7ec Mon Sep 17 00:00:00 2001
From: Sourab Mangrulkar <13534540+pacman100@users.noreply.github.com>
Date: Tue, 4 Apr 2023 20:05:59 +0530
Subject: [PATCH] =?UTF-8?q?=F0=9F=98=85.=20Fix=20=F0=9F=90=9B?=
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---
 src/peft/tuners/lora.py         | 2 +-
 src/peft/utils/save_and_load.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/peft/tuners/lora.py b/src/peft/tuners/lora.py
index 0023717..63201cc 100644
--- a/src/peft/tuners/lora.py
+++ b/src/peft/tuners/lora.py
@@ -404,7 +404,7 @@ class LoraLayer:
             nn.init.zeros_(self.lora_B[adapter_name].weight)
 
 
-class Linear(nn.Linear):
+class Linear(nn.Linear, LoraLayer):
     # Lora implemented in a dense layer
     def __init__(
         self,
diff --git a/src/peft/utils/save_and_load.py b/src/peft/utils/save_and_load.py
index 7ebdfaf..a258c32 100644
--- a/src/peft/utils/save_and_load.py
+++ b/src/peft/utils/save_and_load.py
@@ -53,7 +53,7 @@ def get_peft_model_state_dict(model, state_dict=None, adapter_name="default"):
     elif isinstance(config, PromptLearningConfig):
         to_return = {}
         if config.inference_mode:
-            prompt_embeddings = model.prompt_encoder.embedding.weight
+            prompt_embeddings = model.prompt_encoder[adapter_name].embedding.weight
         else:
             prompt_embeddings = model.get_prompt_embedding_to_save(adapter_name)
         to_return["prompt_embeddings"] = prompt_embeddings