SupraLabs/SupraCMA-8M
Text Generation • 9.08M • Updated • 373 • 8
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A globally shuffled version of HuggingFaceFW/fineweb_edu_100BT.
Part of the Smol-Data collection — tried and tested mixes for strong pretraining.
This dataset contains the same ~100B tokens as fineweb_edu_100BT but with all documents globally shuffled (seed=42). Use this version when you need randomized document ordering for pretraining.
The unshuffled dataset was loaded into memory, shuffled with dataset.shuffle(seed=42), and re-uploaded with 100 shards. See the smol_data.py script for details.
from datasets import load_dataset
ds = load_dataset("HuggingFaceFW/fineweb_edu_100BT-shuffled", split="train", streaming=True)
for sample in ds:
print(sample["text"][:200])
break
@misc{niklaus2026smoldata,
title={SmolData},
author={Joel Niklaus and Hynek Kydl{\'\i}{\v{c}}ek},
year={2026},
publisher={Hugging Face},
journal={Hugging Face repository},
howpublished={\url{https://huggingface.co/collections/HuggingFaceFW/smol-data}}
}