FineWeb2
FineWeb2 applies the ideas behind FineWeb to many languages at once. Rather than reusing English-tuned rules, its pipeline adjusts quality filtering and deduplication (removing duplicate and near-duplicate pages) per language, so smaller languages are cleaned on their own terms rather than by English standards.
The data comes from Common Crawl and is published as Parquet files on HuggingFace, streamable with the `datasets` library so you can work language by language without downloading everything. This makes it a practical foundation for non-English and cross-lingual RAG knowledge bases.
Related sources
C4 (Colossal Clean Crawled Corpus)
A 750 GB English corpus derived from Common Crawl using heuristic cleaning to keep natural language and drop gibberish, boilerplate, and placeholder text. Built to train Google's T5 and later used for MPT-7B and others.
Common Crawl
A nonprofit that crawls the web and freely provides its archives and datasets. Petabytes of raw web data from billions of pages, with a new snapshot each month. Used in the training of GPT-3, LLaMA, T5, and many other large language models.
DCLM-Baseline (DataComp-LM)
A filtered English web dataset from the DataComp-LM benchmark project, produced by running model-based quality filtering over Common Crawl. Built to show which data-curation choices most improve language model training.
Dolma
A 3T token open corpus from Allen AI (its name stands for "Data for Open Language Models' Appetite") combining web text, scientific papers, code, public-domain books, Reddit posts, and Wikipedia. Built to train the OLMo models.