The FineWeb quality-filtering methodology extended to over 1,000 languages (1,868 language-script pairs) — roughly 8TB of compressed, deduplicated web text (~3 trillion words) from 96 CommonCrawl snapshots. Per-language pipelines were tuned and validated so filtered data beats unfiltered in ablation training. The default multilingual pretraining corpus for open models.
Dataset Details
Provider
HuggingFaceFW
Category
Pretraining
Size
8TB Compressed
License
ODC-By 1.0
Downloads
n/a
Tags
Multilingual, CommonCrawl, Deduplicated, 1000+ Languages
from datasets import load_dataset
ds = load_dataset("HuggingFaceFW/fineweb-2")
Related datasets
FineWeb — Pretraining or continued pretraining on high-quality English web text
Aya Dataset — Instruction-tuning in non-English languages with real human-written data
Cosmopedia — Synthetic-textbook pretraining for small models (the SmolLM recipe)
SlimPajama — Efficient English pretraining on a heavily deduplicated corpus
Frequently asked questions
Can I use FineWeb 2 commercially?
Yes — FineWeb 2 is released under ODC-By 1.0, a permissive license that allows commercial use, including training models you ship in a product. Check the dataset card for attribution requirements before release.
How much data does FineWeb 2 contain, and do I need all of it?
FineWeb 2 contains 8TB Compressed. You rarely need all of it: for style and format fine-tuning, a few hundred to a few thousand examples are enough — load a slice (e.g. split="train[:1000]") and scale up only if quality plateaus.
What is FineWeb 2 best used for?
Pretraining or continued pretraining in languages other than English. It belongs to the Pretraining section of our dataset hub, where you'll find alternatives and complementary sets.