#!/usr/bin/env python3 """Download 300GB from HuggingFace datasets - FineWeb, RedPajama, etc.""" import os import json from datasets import load_dataset from huggingface_hub import snapshot_download import time TARGET_GB = 300 OUTPUT_DIR = "/workspace/scraped_data" os.makedirs(OUTPUT_DIR, exist_ok=True) # Best large text datasets on HF DATASETS = [ ("HuggingFaceFW/fineweb", "sample-10BT", None), # ~50GB sample ("togethercomputer/RedPajama-Data-V2", "sample", "en_head_middle"), # ~30GB ("allenai/dolma", "v1_6-sample", None), # ~40GB ("cerebras/SlimPajama-627B", None, None), # Big ] def get_size_gb(): total = 0 for root, dirs, files in os.walk(OUTPUT_DIR): for f in files: total += os.path.getsize(os.path.join(root, f)) return total / 1e9 def download_streaming(name, config, split): """Stream download to avoid OOM""" print(f"\nšŸ“„ Downloading {name} ({config or 'default'})...") try: ds = load_dataset(name, config, split=split or "train", streaming=True, trust_remote_code=True) shard_num = 0 batch = [] batch_size = 10000 for i, example in enumerate(ds): text = example.get("text") or example.get("content") or str(example) batch.append({"text": text, "source": name}) if len(batch) >= batch_size: outfile = f"{OUTPUT_DIR}/{name.replace('/', '_')}_{shard_num:05d}.jsonl" with open(outfile, 'w') as f: for item in batch: f.write(json.dumps(item) + "\n") batch = [] shard_num += 1 size_gb = get_size_gb() print(f" Progress: {size_gb:.1f} GB / {TARGET_GB} GB ({i:,} examples)") if size_gb >= TARGET_GB: print(f"āœ… Target reached!") return True except Exception as e: print(f" Error: {e}") return False if __name__ == "__main__": print(f"šŸš€ Goddess HF Scraper - Target: {TARGET_GB} GB") print(f"Output: {OUTPUT_DIR}") start = time.time() for name, config, split in DATASETS: if get_size_gb() >= TARGET_GB: break done = download_streaming(name, config, split) if done: break elapsed = time.time() - start final_size = get_size_gb() print(f"\n✨ Done! {final_size:.1f} GB in {elapsed/3600:.1f} hours")