Download examples/01_load_paper_scope.py from AgentsSci/AAAI_Wrong-but-Useful: direct link, hf CLI and curl.
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1.58 kB
| #!/usr/bin/env python3 | |
| """Load the paper-scope slice of the private AAAI_Wrong-but-Useful archive. | |
| PRIVATE REPO: run `hf auth login` first, or this fails with 401/403. | |
| """ | |
| import pyarrow.compute as pc | |
| import pyarrow.dataset as ds | |
| from huggingface_hub import snapshot_download | |
| REPO = "AgentsSci/AAAI_Wrong-but-Useful" | |
| # The paper-scope filter. All three clauses matter: | |
| # protocol_id -- the archive is a five-protocol superset | |
| # paper_analysis_eligible -- the strict complete-LOO analysis view | |
| # actor_model_id -- belt-and-braces; excludes evaluator-only gemma3_27b | |
| PAPER = ((pc.field("protocol_id") == "dhd") | |
| & (pc.field("paper_analysis_eligible") == True) # noqa: E712 | |
| & (pc.field("actor_model_id").isin(["gemma_4_31b", "gpt_oss_120b"]))) | |
| def main() -> None: | |
| root = snapshot_download( | |
| REPO, | |
| repo_type="dataset", | |
| allow_patterns=["data/labels/interventional_credit/**", "registry/*.parquet"], | |
| ) | |
| credit = ds.dataset(f"{root}/data/labels/interventional_credit", | |
| format="parquet", partitioning="hive") | |
| print(f"all rows : {credit.count_rows():>9,} credit labels") | |
| print(f"paper scope : {credit.count_rows(filter=PAPER):>9,} credit labels") | |
| for scope, unit in [("committee_hypothesis", "LOO removal events"), | |
| ("individual_hypothesis", "hypotheses")]: | |
| n = credit.count_rows(filter=PAPER & (pc.field("credit_scope") == scope)) | |
| print(f" {scope:<22}: {n:>9,} {unit}") | |
| if __name__ == "__main__": | |
| main() | |