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#!/usr/bin/env python3
"""Upload the prepared viewer files to the Hugging Face Hub."""
from __future__ import annotations
import argparse
import json
from pathlib import Path
from typing import Dict
from datasets import Dataset
ROOT = Path(__file__).resolve().parents[1]
DATA_DIR = ROOT / "data"
CONFIGS = {
"clue": DATA_DIR / "clue" / "train.jsonl",
"mep": DATA_DIR / "mep" / "train.jsonl",
}
def read_stats() -> Dict[str, Dict[str, int]]:
stats_path = DATA_DIR / "stats.json"
if not stats_path.exists():
return {}
with stats_path.open("r", encoding="utf-8") as handle:
return json.load(handle)
def push_config(config_name: str, file_path: Path, repo_id: str, args: argparse.Namespace) -> None:
if not file_path.exists():
raise FileNotFoundError(f"Missing file for config '{config_name}': {file_path}")
print(f"Loading {config_name} from {file_path.relative_to(ROOT)} ...")
dataset = Dataset.from_json(str(file_path))
dataset.push_to_hub(
repo_id=repo_id,
config_name=config_name,
split=args.split,
private=args.private,
token=args.token,
branch=args.branch,
max_shard_size=args.max_shard_size,
)
print(f"✓ Uploaded {config_name}/{args.split} to {repo_id}")
def main() -> None:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--repo", required=True, help="Target dataset repo id, e.g. user/cuebench")
parser.add_argument("--split", default="train", help="Split name to register on the Hub (default: train)")
parser.add_argument("--branch", default=None, help="Optional branch to push to (defaults to repo default)")
parser.add_argument("--token", default=None, help="HuggingFace token; omit if already logged in via CLI")
parser.add_argument("--private", action="store_true", help="Mark the uploaded dataset as private")
parser.add_argument("--max-shard-size", default="500MB", help="Shard threshold passed to push_to_hub")
args = parser.parse_args()
stats = read_stats()
for config_name, path in CONFIGS.items():
push_config(config_name, path, args.repo, args)
if config_name in stats:
summary = stats[config_name]
print(
f" ↳ stats: {summary.get('num_examples', '?')} examples, "
f"{summary.get('num_bytes', '?')} bytes"
)
if __name__ == "__main__":
main()
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