Upload build_dataset.py

build_dataset.py

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+"""Build script for mteb/SlovakSumURLClustering.
+
+This dataset is the MTEB-ready (clustering) version of the SlovakSum dataset,
+used by the `SlovakSumURLClustering` task in
+https://github.com/embeddings-benchmark/mteb.
+
+Source: kiviki/slovaksum-url-clustering (columns: title, sum, theme)
+  https://huggingface.co/datasets/kiviki/slovaksum-url-clustering
+Transform: combine `title` + `sum` into a single `sentences` field, and rename
+  `theme` to `labels` -- the schema MTEB's AbsTaskClustering 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 `SlovakSumURLClustering` 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 Dataset, DatasetDict, load_dataset
+from huggingface_hub import HfApi
+
+SOURCE_REPO = "kiviki/slovaksum-url-clustering"
+SOURCE_REVISION = "6ac67c0a18a641c611c49224a82012cd749000e2"
+TARGET_REPO = "mteb/SlovakSumURLClustering"
+
+
+def build(source_revision: str = SOURCE_REVISION) -> DatasetDict:
+    raw = load_dataset(SOURCE_REPO, revision=source_revision)
+    ds = {}
+    for split in raw:
+        titles = raw[split]["title"]
+        summaries = raw[split]["sum"]
+        sentences = [f"{t} {s}".strip() for t, s in zip(titles, summaries)]
+        labels = raw[split]["theme"]
+        ds[split] = Dataset.from_dict({"sentences": sentences, "labels": labels})
+    return DatasetDict(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()