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The ROOTS Search Tool: Data Transparency for LLMs.

, , , , , , , and . ACL (demo), page 304-314. Association for Computational Linguistics, (2023)

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The ROOTS Search Tool: Data Transparency for LLMs., , , , , , , and . ACL (demo), page 304-314. Association for Computational Linguistics, (2023)The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources., , , , , , , , , and 13 other author(s). CoRR, (2024)The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset., , , , , , , , , and 44 other author(s). CoRR, (2023)Fair Diffusion: Instructing Text-to-Image Generation Models on Fairness., , , , , , and . CoRR, (2023)Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements., , , , , , , , , and . EMNLP (Demos), page 128-136. Association for Computational Linguistics, (2022)Towards Reproducible Machine Learning Research in Natural Language Processing., , , , , , , and . ACL (tutorial), page 7-11. Association for Computational Linguistics, (2022)Energy and Carbon Considerations of Fine-Tuning BERT., , , , and . EMNLP (Findings), page 9058-9069. Association for Computational Linguistics, (2023)StarCoder: may the source be with you!, , , , , , , , , and 57 other author(s). (2023)cite arxiv:2305.06161.Power Hungry Processing: Watts Driving the Cost of AI Deployment?, , and . FAccT, page 85-99. ACM, (2024)StarCoder: may the source be with you!, , , , , , , , , and 57 other author(s). Trans. Mach. Learn. Res., (2023)