Trying to load an external model Llama-30B-Supercot results in below error

### System Info

Langchain version 0.0.179
Ubuntu 20.4


### Who can help?

@hwchase17 @agola11 @vowelparrot 

### Information

- [ ] The official example notebooks/scripts
- [X] My own modified scripts

### Related Components

- [X] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [ ] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [X] Chains
- [ ] Callbacks/Tracing
- [ ] Async

### Reproduction

Trying to load Llama-30b-supercot this way results in below error, what is the correct way to load a model with additional configuration like given below?

```
model_name = 'ausboss/llama-30b-supercot'
quantization_config = BitsAndBytesConfig(llm_int8_enable_fp32_cpu_offload=True)
model = AutoModelForCausalLM.from_pretrained(model_name,
    torch_dtype=torch.float16, device_map='auto', load_in_8bit=True,quantization_config=quantization_config)

tokenizer = AutoTokenizer.from_pretrained(model_name)
  
instruct_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer, torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto", 
                            return_full_text=True, max_new_tokens=200, top_p=0.95, top_k=50, eos_token_id=tokenizer.eos_token_id)

template = """Below is an instruction that describes a task. Write a response that appropriately completes the request.
 
  Instruction: 
  You are an experienced in this solution and your job is to help providing the best answer related to this. 
  Use only information in the following paragraphs to answer the question at the end, do not repeat sentences in your answer. Explain the answer with reference to these paragraphs. If you don't know, say that you do not know.
 
  {context}
 
  Question: {question}
 
  Response:
  """
prompt = PromptTemplate(input_variables=['context', 'question'], template=template)
 
return load_qa_chain(llm=instruct_pipeline, chain_type="map_reduce", prompt=prompt, verbose=False)
```

Results in this error

```
│ /home/ubuntu/lambda_labs/llama-supercot/Search_faiss_llama_30B_supercot.py:59 in build_qa_chain  │
│                                                                                                  │
│    56   """                                                                                      │
│    57   prompt = PromptTemplate(input_variables=['context', 'question'], template=template)      │
│    58                                                                                            │
│ ❱  59   return load_qa_chain(llm=instruct_pipeline, chain_type="map_reduce", prompt=prompt, ve   │
│    60                                                                                            │
│    61 # Building the chain will load Dolly and can take several minutes depending on the model   │
│    62 qa_chain = build_qa_chain()                                                                │
│                                                                                                  │
│ /home/ubuntu/miniconda/lib/python3.10/site-packages/langchain/chains/question_answering/__init__ │
│ .py:218 in load_qa_chain                                                                         │
│                                                                                                  │
│   215 │   │   │   f"Got unsupported chain type: {chain_type}. "                                  │
│   216 │   │   │   f"Should be one of {loader_mapping.keys()}"                                    │
│   217 │   │   )                                                                                  │
│ ❱ 218 │   return loader_mapping[chain_type](                                                     │
│   219 │   │   llm, verbose=verbose, callback_manager=callback_manager, **kwargs                  │
│   220 │   )                                                                                      │
│   221                                                                                            │
│                                                                                                  │
│ /home/ubuntu/miniconda/lib/python3.10/site-packages/langchain/chains/question_answering/__init__ │
│ .py:95 in _load_map_reduce_chain                                                                 │
│                                                                                                  │
│    92 │   _combine_prompt = (                                                                    │
│    93 │   │   combine_prompt or map_reduce_prompt.COMBINE_PROMPT_SELECTOR.get_prompt(llm)        │
│    94 │   )                                                                                      │
│ ❱  95 │   map_chain = LLMChain(                                                                  │
│    96 │   │   llm=llm,                                                                           │
│    97 │   │   prompt=_question_prompt,                                                           │
│    98 │   │   verbose=verbose,                                                                   │
│                                                                                                  │
│ /home/ubuntu/lambda_labs/llama-supercot/pydantic/main.py:341 in pydantic.main.BaseModel.__init__ │
│                                                                                                  │
│ [Errno 2] No such file or directory: '/home/ubuntu/lambda_labs/llama-supercot/pydantic/main.py'  │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ValidationError: 1 validation error for LLMChain
llm
  value is not a valid dict (type=type_error.dict)
```

### Expected behavior

A model should load for Q&A with documents