I am new to Langchain and i got one error while I gave local fine-tune LLM in but it gave error

[Hiren838]

model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"

Function to set up the conversational retrieval chain

def get_conversation_chain(vectorstore):
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, load_in_8bit=False,
device_map="cpu",
trust_remote_code=True)
model_path = "model_checkpoints/checkpoint-876"
peft_model = PeftModel.from_pretrained(model, model_path, from_transformers=True, device_map="cpu")
model = peft_model.merge_and_unload()
memory = ConversationBufferMemory(
memory_key='chat_history', return_messages=True
)
conversation_chain = ConversationalRetrievalChain.from_llm(
llm=model,
retriever=vectorstore.as_retriever(),
memory=memory
)
return conversation_chain

this error i got

ValidationError
pydantic.v1.error_wrappers.ValidationError: 2 validation errors for LLMChain
llm
instance of Runnable expected (type=type_error.arbitrary_type; expected_arbitrary_type=Runnable)
llm
instance of Runnable expected (type=type_error.arbitrary_type; expected_arbitrary_type=Runnable)