diff --git a/requirements.txt b/requirements.txt
index e7f5bf16..12e907e5 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -10,7 +10,7 @@ rouge-chinese
 nltk
 gradio>=3.36.0
 uvicorn
-pydantic
-fastapi
+pydantic==1.10.11
+fastapi==0.95.1
 sse-starlette
 matplotlib
diff --git a/src/llmtuner/__init__.py b/src/llmtuner/__init__.py
index b53af4de..fde74f57 100644
--- a/src/llmtuner/__init__.py
+++ b/src/llmtuner/__init__.py
@@ -4,4 +4,4 @@ from llmtuner.tuner import get_train_args, get_infer_args, load_model_and_tokeni
 from llmtuner.webui import create_ui
 
 
-__version__ = "0.1.0"
+__version__ = "0.1.1"
diff --git a/src/llmtuner/api/app.py b/src/llmtuner/api/app.py
index 2a07527a..63b4fd10 100644
--- a/src/llmtuner/api/app.py
+++ b/src/llmtuner/api/app.py
@@ -1,4 +1,3 @@
-import json
 import uvicorn
 from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
@@ -96,7 +95,7 @@ def create_app():
             finish_reason=None
         )
         chunk = ChatCompletionStreamResponse(model=request.model, choices=[choice_data])
-        yield json.dumps(chunk, ensure_ascii=False)
+        yield chunk.json(exclude_unset=True, ensure_ascii=False)
 
         for new_text in chat_model.stream_chat(
             query, history, prefix, temperature=request.temperature, top_p=request.top_p, max_new_tokens=request.max_tokens
@@ -110,7 +109,7 @@ def create_app():
                 finish_reason=None
             )
             chunk = ChatCompletionStreamResponse(model=request.model, choices=[choice_data])
-            yield json.dumps(chunk, ensure_ascii=False)
+            yield chunk.json(exclude_unset=True, ensure_ascii=False)
 
         choice_data = ChatCompletionResponseStreamChoice(
             index=0,
@@ -118,7 +117,7 @@ def create_app():
             finish_reason=Finish.STOP
         )
         chunk = ChatCompletionStreamResponse(model=request.model, choices=[choice_data])
-        yield json.dumps(chunk, ensure_ascii=False)
+        yield chunk.json(exclude_unset=True, ensure_ascii=False)
         yield "[DONE]"
 
     return app
diff --git a/src/llmtuner/tuner/ppo/trainer.py b/src/llmtuner/tuner/ppo/trainer.py
index 0d84af6e..668d2f44 100644
--- a/src/llmtuner/tuner/ppo/trainer.py
+++ b/src/llmtuner/tuner/ppo/trainer.py
@@ -107,7 +107,11 @@ class PPOPeftTrainer(PPOTrainer, PeftTrainer):
             # Compute rewards
             replace_model(unwrapped_model, target="reward")
             with torch.no_grad():
-                _, _, values = self.model(**self.prepare_model_inputs(queries, responses))
+                _, _, values = self.model(
+                    **self.prepare_model_inputs(queries, responses),
+                    output_hidden_states=True,
+                    return_dict=True
+                )
             rewards = [reward for reward in values[:, -1].to(torch.float32)] # use float32 type
             replace_model(unwrapped_model, target="default")
 
diff --git a/src/llmtuner/tuner/rm/trainer.py b/src/llmtuner/tuner/rm/trainer.py
index 199fecf4..749fa68d 100644
--- a/src/llmtuner/tuner/rm/trainer.py
+++ b/src/llmtuner/tuner/rm/trainer.py
@@ -32,7 +32,7 @@ class PairwisePeftTrainer(PeftTrainer):
         See: https://github.com/huggingface/transformers/blob/v4.30.2/src/transformers/trainer.py#L3509
         """
         batch_size = inputs["input_ids"].size(0) // 2
-        _, _, values = model(**inputs)
+        _, _, values = model(**inputs, output_hidden_states=True, return_dict=True)
         r_accept, r_reject = values[:, -1].split(batch_size, dim=0)
         loss = -torch.log(torch.sigmoid(r_accept - r_reject)).mean()
         return (loss, [loss, r_accept, r_reject]) if return_outputs else loss