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| """Entraîne M.O.U.H. Lancement : | |
| python scripts/train.py --preset mouh-tiny --data ./corpus --max_steps 200 | |
| torchrun --nproc_per_node=8 scripts/train.py --preset mouh-1.5b --data <dataset_hub> --parallel fsdp | |
| """ | |
| import argparse | |
| import dataclasses | |
| import sys | |
| from pathlib import Path | |
| sys.path.insert(0, str(Path(__file__).resolve().parents[1])) | |
| from mouh.training import TrainArgs, train # noqa: E402 | |
| def main() -> None: | |
| ap = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) | |
| for f in dataclasses.fields(TrainArgs): | |
| t = f.type if isinstance(f.type, type) else str | |
| if f.name == "betas": | |
| ap.add_argument("--betas", type=float, nargs=2, default=list(f.default)) | |
| elif f.type in (bool, "bool"): | |
| ap.add_argument(f"--{f.name}", action="store_true", default=f.default) | |
| else: | |
| ap.add_argument(f"--{f.name}", type={"int": int, "float": float}.get(str(f.type), str), default=f.default) | |
| ns = vars(ap.parse_args()) | |
| ns["betas"] = tuple(ns["betas"]) | |
| print(train(TrainArgs(**ns))) | |
| if __name__ == "__main__": | |
| main() | |