code: def prepare_sample_text(example):
      """Prepare the text from a sample of the dataset."""
      text = f"Question: {example['question']}\n\nAnswer: {example['response_j']}"
      return text
  
file_path: trl/examples/research_projects/stack_llama_2/scripts/sft_llama2.py
imports: import os
  from dataclasses import dataclass, field
  from typing import Optional
  import torch
  from accelerate import Accelerator
  from datasets import load_dataset
  from peft import AutoPeftModelForCausalLM, LoraConfig
  from tqdm import tqdm
  from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, HfArgumentParser, TrainingArguments
  from trl import SFTTrainer
  from trl.import_utils import is_npu_available, is_xpu_available
  from trl.trainer import ConstantLengthDataset
label_desc: Use image node_id 3 for calling a global function with example usage: prepare_sample_text(example) and returns: text