FineWeb 2 — LLM Pretraining Dataset
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.
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