code: def generate_prompt(data_point):
      # sorry about the formatting disaster gotta move fast
      if data_point["input"]:
          return f"""Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.  # noqa: E501
  
  ### Instruction:
  {data_point["instruction"]}
  
  ### Input:
  {data_point["input"]}
  
  ### Response:
  {data_point["output"]}"""
      else:
          return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request.  # noqa: E501
  
  ### Instruction:
  {data_point["instruction"]}
  
  ### Response:
  {data_point["output"]}"""
  
file_path: BigDL/docker/llm/finetune/lora/cpu/docker/lora_finetune.py
imports: import os
  import sys
  from typing import List
  import time
  import fire
  import torch
  from torch.utils.data import DataLoader
  import transformers
  from datasets import load_dataset
  from peft import LoraConfig, get_peft_model, get_peft_model_state_dict, prepare_model_for_int8_training, set_peft_model_state_dict
  from transformers import LlamaForCausalLM, LlamaTokenizer
  from transformers import BitsAndBytesConfig
label_desc: Use image node_id 2 for calling a global function with example usage: generate_prompt(data_point) and returns: str, data_point, str, data_point, str, data_point, str, data_point, str, data_point