code: def load_file_path(
      model_name_or_path: str,
      filename: str,
      token: Optional[Union[bool, str]],
      cache_folder: Optional[str],
  ) -> Optional[str]:
      # If file is local
      file_path = os.path.join(model_name_or_path, filename)
      if os.path.exists(file_path):
          return file_path
  
      # If file is remote
      try:
          return hf_hub_download(
              model_name_or_path,
              filename=filename,
              library_name="sentence-transformers",
              token=token,
              cache_dir=cache_folder,
          )
      except Exception:
          return
  
imports: import functools
  import requests
  from torch import Tensor, device
  from typing import List, Callable
  from tqdm.autonotebook import tqdm
  import sys
  import importlib
  import os
  import torch
  import numpy
  import queue
  import logging
  from typing import Dict, Optional, Union
  from huggingface_hub import snapshot_download, hf_hub_download
  import heapq
label_desc: Use image node_id 17 for calling a global function with example usage: load_file_path(model_name_or_path, filename, token, cache_folder) and returns: file_path, hf_hub_download