fd3b80716a
* remove fastchat and sharegpt * remove imports * remove more fastchat imports * chore: remove unused functions * feat: remove sharegpt and deprecate from docs * chore: remove unused sharegpt checks * fix: remove sharegpt type from tests * feat: add sharegpt deprecation error * feat: update readme --------- Co-authored-by: NanoCode012 <nano@axolotl.ai>
85 lines
2.7 KiB
Python
85 lines
2.7 KiB
Python
"""
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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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import warnings
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from pathlib import Path
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from typing import Union
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import fire
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import transformers
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from accelerate import init_empty_weights
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from colorama import Fore
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from dotenv import load_dotenv
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from transformers import AutoModelForCausalLM
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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 PreprocessCliArgs
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from axolotl.common.const import DEFAULT_DATASET_PREPARED_PATH
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from axolotl.utils.trainer import disable_datasets_caching
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LOG = logging.getLogger("axolotl.cli.preprocess")
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def do_cli(config: Union[Path, str] = Path("examples/"), **kwargs):
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# pylint: disable=duplicate-code
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print_axolotl_text_art()
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parsed_cfg = load_cfg(config, **kwargs)
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parsed_cfg.is_preprocess = True
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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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with disable_datasets_caching():
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if parsed_cfg.rl: # and parsed_cfg.rl != "orpo":
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load_rl_datasets(cfg=parsed_cfg, cli_args=parsed_cli_args)
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else:
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load_datasets(cfg=parsed_cfg, cli_args=parsed_cli_args)
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if parsed_cli_args.download:
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model_name = parsed_cfg.base_model
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with warnings.catch_warnings():
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# there are a bunch of useless UserWarnings about
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# "copying from a non-meta parameter in the checkpoint to a meta parameter in the current model"
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warnings.simplefilter("ignore")
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with init_empty_weights(include_buffers=True):
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# fmt: off
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try:
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AutoModelForCausalLM.from_pretrained(
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model_name, trust_remote_code=True
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)
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except Exception as exc: # pylint: disable=broad-exception-caught,unused-variable # nosec B110 # noqa F841
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pass
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# fmt: on
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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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load_dotenv()
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fire.Fire(do_cli)
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