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aacc29a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | """CLI: run a trained QLoRA GEC adapter over pairs to add a prediction column.
python scribe/training/scripts/predict.py \
--pairs artifacts/evaluations/ckey_rag_smoke.jsonl \
--adapter-dir artifacts/gec_lora/qwen3_full \
--output artifacts/evaluations/darag_all_preds.jsonl --column gec_pred
"""
from __future__ import annotations
import argparse
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[3] / "scribe" / "training"))
sys.path.insert(0, str(Path(__file__).resolve().parents[3] / "scribe"))
from gec.cliutil import configure_stdout # noqa: E402
configure_stdout()
from gec.config import DEFAULT_BASE_MODEL, FALLBACK_BASE_MODEL # noqa: E402
from gec.predict import predict_pairs # noqa: E402
def main() -> None:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--pairs", required=True)
parser.add_argument("--adapter-dir", default="artifacts/gec_lora/qwen3_full")
parser.add_argument("--output", required=True)
parser.add_argument("--column", default="gec_pred")
parser.add_argument("--base-model", default=DEFAULT_BASE_MODEL)
parser.add_argument("--fallback-model", default=FALLBACK_BASE_MODEL)
parser.add_argument("--max-new-tokens", type=int, default=256)
parser.add_argument("--limit", type=int, default=None)
retrieval = parser.add_mutually_exclusive_group()
retrieval.add_argument("--use-retrieval", dest="use_retrieval", action="store_true", default=None,
help="Force NEs in the prompt (default: read the adapter's variant marker).")
retrieval.add_argument("--no-retrieval", dest="use_retrieval", action="store_false",
help="Force NEs out of the prompt (matches a wo_rac adapter).")
args = parser.parse_args()
predict_pairs(
pairs_path=Path(args.pairs),
adapter_dir=Path(args.adapter_dir),
output_path=Path(args.output),
column=args.column,
base_model=args.base_model,
fallback_model=args.fallback_model,
use_retrieval=args.use_retrieval,
max_new_tokens=args.max_new_tokens,
limit=args.limit,
)
if __name__ == "__main__":
main()
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