Unlock the full potential of state-of-the-art multilingual LLMs with FineWeb2, a groundbreaking 20 terabyte (5 billion document) dataset. This new pre-training data is generated by a revolutionary curation pipeline that automatically adapts to support any language. Overcoming the inherent difficulty of tailoring filtering and deduplication for a large number of languages, FineWeb2 has been scaled to over 1000 languages using Common Crawl snapshots. It produces more performant models than prior datasets for non-English corpora and includes a principled approach to rebalance datasets for additional performance uplift. Access the released dataset, pipeline, training, and evaluation codebases today!

This comprehensive review systematically analyzes data center energy consumption and reliability modeling, providing a state-of-the-art overview and identifying crucial research gaps. It classifies and examines energy consumption models for major load sections, including information technology (IT), internal power conditioning systems (IPCS), and cooling, outlining their applications, advantages, and disadvantages.