Upload build_dataset.py

build_dataset.py

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+"""Build script for mteb/SlovakSTS.
+
+This dataset is the MTEB-ready (STS) version of the sklep STS benchmark, used by
+the `SlovakSTS` task in https://github.com/embeddings-benchmark/mteb.
+
+Source: slovak-nlp/sklep, config "sts" (columns include: sentence1, sentence2,
+  similarity_score, plus sentence1_orig/sentence2_orig which MTEB does not use)
+  https://huggingface.co/datasets/slovak-nlp/sklep
+Transform: rename `similarity_score` -> `score` (cast to float), and select only
+  `sentence1`/`sentence2`/`score` -- the schema MTEB's AbsTaskSTS expects.
+
+If the source dataset publishes a new revision, regenerate this dataset with:
+    python build_dataset.py --source-revision <new-sha> --token $HF_TOKEN
+
+then update the `SlovakSTS` task's `dataset.path`/`revision` in mteb to the new
+revision this script prints on push.
+"""
+
+from __future__ import annotations
+
+import argparse
+
+from datasets import DatasetDict, load_dataset
+from huggingface_hub import HfApi
+
+SOURCE_REPO = "slovak-nlp/sklep"
+SOURCE_CONFIG = "sts"
+SOURCE_REVISION = "10549a8c63542e6a0db4fcf5fcdc29b3e1b8c4e9"
+TARGET_REPO = "mteb/SlovakSTS"
+
+
+def build(source_revision: str = SOURCE_REVISION) -> DatasetDict:
+    raw = load_dataset(SOURCE_REPO, SOURCE_CONFIG, revision=source_revision)
+    ds = raw.rename_columns({"similarity_score": "score"})
+    ds = ds.map(lambda example: {"score": float(example["score"])})
+    ds = ds.select_columns(["sentence1", "sentence2", "score"])
+    return ds
+
+
+def main() -> None:
+    p = argparse.ArgumentParser(description=__doc__)
+    p.add_argument("--source-revision", default=SOURCE_REVISION)
+    p.add_argument("--repo", default=TARGET_REPO)
+    p.add_argument("--token", default=None, help="HF token (or use HF_TOKEN env / `huggingface-cli login`).")
+    p.add_argument("--private", action="store_true")
+    p.add_argument("--dry-run", action="store_true")
+    args = p.parse_args()
+
+    ds = build(args.source_revision)
+    for split, d in ds.items():
+        print(f"  split={split} rows={len(d)} columns={d.column_names}")
+
+    if args.dry_run:
+        print(f"[dry-run] would push to {args.repo}")
+        return
+
+    ds.push_to_hub(
+        args.repo,
+        commit_message="Rebuild from source revision",
+        token=args.token,
+        private=args.private,
+    )
+    revision = HfApi(token=args.token).dataset_info(args.repo).sha
+    print(f"-> pushed to {args.repo}, revision={revision}")
+
+
+if __name__ == "__main__":
+    main()