()
| 231 | |
| 232 | |
| 233 | def main(): |
| 234 | parser = argparse.ArgumentParser() |
| 235 | |
| 236 | # Required parameters |
| 237 | parser.add_argument( |
| 238 | "--model_name_or_path", |
| 239 | default=None, |
| 240 | type=str, |
| 241 | required=True, |
| 242 | help="Path to pre-trained model or shortcut name", |
| 243 | ) |
| 244 | parser.add_argument( |
| 245 | "--output_dir", |
| 246 | default=None, |
| 247 | type=str, |
| 248 | required=True, |
| 249 | help="The output directory where the model checkpoints and predictions will be written.", |
| 250 | ) |
| 251 | |
| 252 | # Other parameters |
| 253 | parser.add_argument( |
| 254 | "--data_dir", |
| 255 | default=None, |
| 256 | type=str, |
| 257 | help="The input data dir. Should contain the .json files for the task." |
| 258 | + "If no data dir or train/predict files are specified, will run with tensorflow_datasets.", |
| 259 | ) |
| 260 | parser.add_argument( |
| 261 | "--train_file", |
| 262 | default=None, |
| 263 | type=str, |
| 264 | help="The input training file. If a data dir is specified, will look for the file there" |
| 265 | + "If no data dir or train/predict files are specified, will run with tensorflow_datasets.", |
| 266 | ) |
| 267 | parser.add_argument( |
| 268 | "--predict_file", |
| 269 | default=None, |
| 270 | type=str, |
| 271 | help="The input evaluation file. If a data dir is specified, will look for the file there" |
| 272 | + "If no data dir or train/predict files are specified, will run with tensorflow_datasets.", |
| 273 | ) |
| 274 | parser.add_argument( |
| 275 | "--config_name", default="", type=str, help="Pretrained config name or path if not the same as model_name" |
| 276 | ) |
| 277 | parser.add_argument( |
| 278 | "--tokenizer_name", |
| 279 | default="", |
| 280 | type=str, |
| 281 | help="Pretrained tokenizer name or path if not the same as model_name", |
| 282 | ) |
| 283 | parser.add_argument( |
| 284 | "--cache_dir", |
| 285 | default="", |
| 286 | type=str, |
| 287 | help="Where do you want to store the pre-trained models downloaded from s3", |
| 288 | ) |
| 289 | |
| 290 | parser.add_argument( |
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