code: def pull_from_hub(
      specifier: str,
      model_name: str,
      adapter_config: Optional[Union[dict, str]] = None,
      version: str = None,
      strict: bool = False,
      **kwargs,
  ) -> str:
      """
      Downloads a pre-trained adapter module from Adapter-Hub
  
      Args:
          specifier (str): A string specifying the adapter to be loaded.
          model_name (str): The identifier of the pre-trained model for which to load an adapter.
          adapter_config (Union[dict, str], optional): The configuration of the adapter to be loaded.
          version (str, optional): The version of the adapter to be loaded. Defaults to None.
          strict (bool, optional):
              If set to True, only allow adapters exactly matching the given config to be loaded. Defaults to False.
  
      Returns:
          str: The local path to which the adapter has been downloaded.
      """
      if not model_name:
          raise ValueError(
              "Unable to resolve adapter without the name of a model. Please specify model_name."
          )
      # resolve config if it's an identifier
      if adapter_config:
          adapter_config = resolve_adapter_config(adapter_config)
      # search the correct entry in the index
      hub_entry_url = find_in_index(
          specifier,
          model_name,
          adapter_config=adapter_config,
          strict=strict,
      )
      if not hub_entry_url:
          raise EnvironmentError(
              "No adapter with name '{}' was found in the adapter index.".format(
                  specifier
              )
          )
      hub_entry = http_get_json(hub_entry_url)
  
      # set version
      if not version:
          version = hub_entry["default_version"]
      elif version not in hub_entry["files"]:
          logger.warn(
              "Version '{}' of adapter '{}' not found. Falling back to default.".format(
                  version, specifier
              )
          )
          version = hub_entry["default_version"]
      file_entry = hub_entry["files"][version]
  
      # start downloading
      logger.info(
          "Resolved adapter files at {}.".format(file_entry["url"])
      )
      checksum_algo, checksum = get_checksum(file_entry)
      download_path = download_cached(
          file_entry["url"],
          checksum=checksum,
          checksum_algo=checksum_algo,
          **kwargs,
      )
      if not download_path:
          raise EnvironmentError(
              "Unable to load file from {}. The file might be unavailable.".format(
                  file_entry["url"]
              )
          )
      return download_path
  
imports: import ast
  import fnmatch
  import hashlib
  import inspect
  import io
  import json
  import logging
  import os
  import re
  import shutil
  import tarfile
  import tempfile
  from collections.abc import Mapping
  from contextlib import contextmanager
  from dataclasses import dataclass
  from enum import Enum
  from functools import partial
  from os.path import basename, isdir, isfile, join
  from pathlib import Path
  from typing import Callable, Dict, List, Optional, Tuple, Union
  from urllib.parse import urlparse
  from zipfile import ZipFile, is_zipfile
  import torch
  import requests
  from filelock import FileLock
  from huggingface_hub import HfApi, HfFolder, snapshot_download
  from huggingface_hub.file_download import http_get, url_to_filename
  from huggingface_hub.utils import EntryNotFoundError, RepositoryNotFoundError, RevisionNotFoundError, hf_raise_for_status
  from requests.exceptions import HTTPError
  from transformers.utils import http_user_agent, is_remote_url
  from transformers.utils.hub import torch_cache_home
  from .None import __version__
  from .context import ForwardContext
label_desc: Use image node_id 16 for calling a global function with example usage: pull_from_hub(specifier, model_name, adapter_config, version, strict) and returns: download_path