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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 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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load_rl_datasets, |
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print_axolotl_text_art, |
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) |
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from axolotl.common.cli import TrainerCliArgs |
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from axolotl.train import train |
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LOG = logging.getLogger("axolotl.cli.train") |
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def do_cli(config: Path = Path("examples/"), **kwargs): |
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parsed_cfg = load_cfg(config, **kwargs) |
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print_axolotl_text_art() |
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check_accelerate_default_config() |
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check_user_token() |
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parser = transformers.HfArgumentParser((TrainerCliArgs)) |
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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 parsed_cfg.rl: |
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dataset_meta = load_rl_datasets(cfg=parsed_cfg, cli_args=parsed_cli_args) |
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else: |
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dataset_meta = load_datasets(cfg=parsed_cfg, cli_args=parsed_cli_args) |
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train(cfg=parsed_cfg, cli_args=parsed_cli_args, dataset_meta=dataset_meta) |
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if __name__ == "__main__": |
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fire.Fire(do_cli) |
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