code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Eval the finetued SFT model"
      )
      parser.add_argument(
          "--model_name_or_path_baseline",
          type=str,
          help="Path to baseline model",
          required=True,
      )
      parser.add_argument(
          "--model_name_or_path_finetune",
          type=str,
          help="Path to pretrained model",
          required=True,
      )
      parser.add_argument(
          "--num_beams",
          type=int,
          default=1,
          help="Specify num of beams",
      )
      parser.add_argument(
          "--num_beam_groups",
          type=int,
          default=1,
          help="Specify num of beams",
      )
      parser.add_argument(
          "--top_k",
          type=int,
          default=4,
          help="Specify num of beams",
      )
      parser.add_argument(
          "--penalty_alpha",
          type=float,
          default=0.6,
          help="Specify num of beams",
      )
      parser.add_argument(
          "--num_return_sequences",
          type=int,
          default=1,
          help="Specify num of return sequences",
      )
      parser.add_argument(
          "--max_new_tokens",
          type=int,
          default=100,
          help="Specify num of return sequences",
      )
      parser.add_argument(
          "--language",
          type=str,
          default="English",
          choices=["English", "Chinese", "Japanese"],
      )
      parser.add_argument(
          "--add_eot_token",
          action="store_true",
          help="Add <|endoftext|> as additional special token to tokenizer",
      )
  
      args = parser.parse_args()
  
      return args
  
file_path: deepspeedexamples/applications/DeepSpeed-Chat/training/step1_supervised_finetuning/prompt_eval.py
imports: import argparse
  import logging
  import torch
  from transformers import AutoModelForCausalLM
  from dschat.utils.model.model_utils import create_hf_model
  from dschat.utils.utils import load_hf_tokenizer
  from deepspeed import get_accelerator
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args