code: def main():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--input_dir",
          help="Location of Mixtral weights, which contains tokenizer.model and model folders",
          required=True,
      )
      parser.add_argument(
          "--model_size",
          choices=["7B"],
          help="'f' models correspond to the finetuned versions, and are specific to the Mixtral official release. For more details on Mixtral, checkout the original repo: https://huggingface.co/mistral-ai",
          default="7B",
      )
      parser.add_argument(
          "--output_dir",
          help="Location to write HF model",
          required=True,
      )
      parser.add_argument(
          "--safe_serialization",
          type=bool,
          help="Whether or not to save using `safetensors`.",
      )
      args = parser.parse_args()
      write_model(
          model_path=args.output_dir,
          input_base_path=args.input_dir,
          model_size=args.model_size,
          safe_serialization=args.safe_serialization,
      )
  
file_path: transformers/src/transformers/models/mixtral/convert_mixtral_weights_to_hf.py
imports: import argparse
  import json
  import os
  import torch
  from transformers import MixtralConfig, MixtralForCausalLM
label_desc: Use image node_id 5 for calling a global function with example usage: main() without return types