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""" |
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CLI to run training on a model |
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""" |
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import logging |
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from pathlib import Path |
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import fire |
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import transformers |
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from colorama import Fore |
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from axolotl.cli import ( |
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check_accelerate_default_config, |
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check_user_token, |
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load_cfg, |
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load_datasets, |
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print_axolotl_text_art, |
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) |
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from axolotl.common.cli import PreprocessCliArgs |
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from axolotl.common.const import DEFAULT_DATASET_PREPARED_PATH |
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LOG = logging.getLogger("axolotl.cli.preprocess") |
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def do_cli(config: Path = Path("examples/"), **kwargs): |
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print_axolotl_text_art() |
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parsed_cfg = load_cfg(config, **kwargs) |
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check_accelerate_default_config() |
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check_user_token() |
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parser = transformers.HfArgumentParser((PreprocessCliArgs)) |
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parsed_cli_args, _ = parser.parse_args_into_dataclasses( |
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return_remaining_strings=True |
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) |
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if not parsed_cfg.dataset_prepared_path: |
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msg = ( |
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Fore.RED |
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+ "preprocess CLI called without dataset_prepared_path set, " |
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+ f"using default path: {DEFAULT_DATASET_PREPARED_PATH}" |
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+ Fore.RESET |
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) |
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LOG.warning(msg) |
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parsed_cfg.dataset_prepared_path = DEFAULT_DATASET_PREPARED_PATH |
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_ = load_datasets(cfg=parsed_cfg, cli_args=parsed_cli_args) |
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LOG.info( |
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Fore.GREEN |
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+ f"Success! Preprocessed data path: `dataset_prepared_path: {parsed_cfg.dataset_prepared_path}`" |
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+ Fore.RESET |
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) |
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if __name__ == "__main__": |
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fire.Fire(do_cli) |
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