Get model from huggingface, modelscope or openmind_hub.
(pretrained_model_name_or_path: str, download_dir: str = None, revision: str = None, token: str = None)
| 253 | |
| 254 | |
| 255 | def get_model(pretrained_model_name_or_path: str, download_dir: str = None, revision: str = None, token: str = None): |
| 256 | """Get model from huggingface, modelscope or openmind_hub.""" |
| 257 | import os |
| 258 | if os.getenv('LMDEPLOY_USE_MODELSCOPE', 'False').lower() == 'true': |
| 259 | from modelscope import snapshot_download |
| 260 | elif os.getenv('LMDEPLOY_USE_OPENMIND_HUB', 'False').lower() == 'true': |
| 261 | from openmind_hub import snapshot_download |
| 262 | else: |
| 263 | from huggingface_hub import snapshot_download |
| 264 | |
| 265 | download_kwargs = {} |
| 266 | if download_dir is not None: |
| 267 | download_kwargs['cache_dir'] = download_dir |
| 268 | if revision is not None: |
| 269 | download_kwargs['revision'] = revision |
| 270 | if token is not None: |
| 271 | download_kwargs['token'] = token |
| 272 | |
| 273 | model_path = snapshot_download(pretrained_model_name_or_path, ignore_patterns=['*.pth'], **download_kwargs) |
| 274 | return model_path |
| 275 | |
| 276 | |
| 277 | def logging_timer(op_name: str, logger: Logger, level: int = logging.DEBUG): |
no outgoing calls
no test coverage detected