tiiuae/falcon-40b-instruct · Unable to load and run finetuned falcon model

Hi everyone,
I have a finetuned model that i have tested on colab and it runs without any issue. I am trying to do the same locally but I gettting some issues.

ValueError: The current 'device_map'  had weights offloaded to the disk. Please provide an 'offload_folder' for them. Alternatively, make sure you have 'safe tensors' installed if the model you are using offers weights in this format

I added the offload folder as suggested but still unable to run the model successfully. Below is the code:

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel, PeftConfig
import torch


def load_peft_model():
    peft_model_id = "DioulaD/falcon-7b-instruct-qlora-ge-dq-v2"    
    model = AutoModelForCausalLM.from_pretrained(
            "tiiuae/falcon-7b-instruct",
            torch_dtype=torch.bfloat16,
            device_map="auto",
            trust_remote_code=True,
            offload_folder = "offload",
            offload_state_dict = True
        )
    model = PeftModel.from_pretrained(model, peft_model_id, offload_folder="offload" )
    model = model.merge_and_unload()
    

    config = PeftConfig.from_pretrained(peft_model_id)

    tknizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
    tknizer.pad_token = tknizer.eos_token
    return model, tknizer

def get_expectations(prompt, model, tknizer):
  """
  Convert natural language query to great expectation methods using finetuned falcon 7b
  Params:
    prompt : Natural language query
    model : Model download from huggingface hub
    tknizer = Tokenizer from peft model
  """
  try:
    # If CUDA support is not available, encoding will silenty fail if cuda:0 is hardcoded
    if torch.cuda.is_available():
      device = 'cuda:0'
    else:
      device = 'cpu'
    
    encoding = tknizer(prompt, return_tensors="pt").to(device)
    model.to(device)

    with torch.inference_mode():
      out = model.generate(
          input_ids=encoding.input_ids,
          attention_mask=encoding.attention_mask,
          max_new_tokens=100, do_sample=True, temperature=0.3,
          eos_token_id=tknizer.eos_token_id,
          top_k=0
      )
    response = tknizer.decode(out[0], skip_special_tokens=True)
    return response.split("\n")[1]

  except Exception as e:
    print("An error occurred: ", e)

model, tknizer = load_peft_model()
prompt = "Verify that the userID column does not contain null values"
output = get_expectations(prompt, model, tknizer)

I added model.to(device) because I was getting an error (inputs_ids was on cuda and model on cpu). No I am getting the following error:

An error occurred:  Cannot copy out of meta tensor; no data!

Thanks in advance for you help!