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      "statement": "# RefinedWeb: scaled filtering and deduplication for web-only pretraining\n\nCombined text extraction, document/line filtering and exact/fuzzy deduplication at web scale, releasing a600B-token extract and studying web-only language-model pretraining against curated-corpus baselines.\n\n## Scientific scope\n\nFive-trillion-token internal corpus differs from released600B-token extract. Controlled reported model comparisons do not prove curated non-web data is never useful or all downstream tasks improve. Distinct from Falcon model architecture; inherited extraction/MinHash methods retain credit.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nGuilherme Penedo; Quentin Malartic; Daniel Hesslow; Ruxandra Cojocaru; Alessandro Cappelli; Hamza Alobeidli; Baptiste Pannier; Ebtesam Almazrouei; Julien Launay\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only](https://arxiv.org/abs/2306.01116v1)\n",
      "summary": "Combined text extraction, document/line filtering and exact/fuzzy deduplication at web scale, releasing a600B-token extract and studying web-only language-model pretraining against curated-corpus baselines.",
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