code: def download_model(
      model_id: str,
      bucket_uri: str,
      s3_sync_args: Optional[List[str]] = None,
      tokenizer_only: bool = False,
  ) -> None:
      """
      Download a model from an S3 bucket and save it in TRANSFORMERS_CACHE for
      seamless interoperability with Hugging Face's Transformers library.
  
      The downloaded model may have a 'hash' file containing the commit hash corresponding
      to the commit on Hugging Face Hub.
      """
      s3_sync_args = s3_sync_args or []
      path = get_download_path(model_id)
  
      cmd = (
          ["awsv2", "s3", "sync"]
          + s3_sync_args
          + (
              ["--exclude", "*", "--include", "*token*"]
              if tokenizer_only
              else []
          )
          + [bucket_uri, path]
      )
      print(f"RUN({cmd})")
      subprocess.run(cmd)
      print("done")
  
file_path: ray/doc/source/templates/04_finetuning_llms_with_deepspeed/utils.py
imports: from typing import List, Optional
  import os
  import subprocess
  import logging
label_desc: Use image node_id 4 for calling a global function with example usage: download_model(model_id, bucket_uri, s3_sync_args, tokenizer_only) without return types