Add config-driven pipeline CLI; make the example configs executable#9
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python -m labelbank.run --cfg <yaml> now drives the full retriever loop (zero-shot eval -> rank bank -> mine gold-first pools -> retrain -> re-evaluate, for mining_rounds rounds; saves adapter, per-split rankings.parquet and metrics.json) and a reranker stage that consumes the rankings parquet. Both example configs are rewritten to the CLI schema they now actually drive. README install matrix gains the existing [rerank] extra; competition write-up public-LB typo fixed (0.54 -> 0.56, matching the two other mentions).
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Closes the gap where
examples/configs/*.yamlhad no consumer in the codebase:python -m labelbank.run --cfg <yaml>—stage: retrieverruns the full loop the README describes (zero-shot eval → rank the whole bank →gold_firstpool mining → contrastive retrain → re-evaluate, formining_roundsrounds), saving the adapter, per-splitrankings.parquetandmetrics.json.stage: rerankerconsumes that parquet and trains the listwise reranker (completion-only, gold position shuffled). Rounds continue one adapter; the docstring notes the competition's fresh-per-round protocol (measured separately in the upcoming experiment example).reproduce_competition.yamlkeeps the original v0 hyperparameters incl. pool 50, NF4, the Eedi instruct prefix, fold-0 eval); a test asserts the shipped configs load.[rerank]extra; pipeline section shows the two CLI one-liners.competition/README.md: public-LB typo in the intro fixed (0.54 → 0.56, matching the two other mentions in the same write-up).🤖 Generated with Claude Code