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  <p>For attribution in academic contexts, please cite this work as</p>
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  <pre class="citation short">Penedo, et al., "The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale", 2024.</pre>
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  <p>BibTeX citation</p>
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- <pre class="citation long">@misc{penedo2024finewebdatasetsdecantingweb,
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- title={The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale},
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- author={Guilherme Penedo and Hynek Kydlíček and Loubna Ben allal and Anton Lozhkov and Margaret Mitchell and Colin Raffel and Leandro Von Werra and Thomas Wolf},
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- year={2024},
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- eprint={2406.17557},
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- archivePrefix={arXiv},
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- primaryClass={cs.CL}
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- url={https://arxiv.org/abs/2406.17557},
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  }</pre>
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  </d-appendix>
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  <p>For attribution in academic contexts, please cite this work as</p>
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  <pre class="citation short">Penedo, et al., "The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale", 2024.</pre>
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  <p>BibTeX citation</p>
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+ <pre class="citation long">@inproceedings{
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+ penedo2024the,
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+ title={The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale},
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+ author={Guilherme Penedo and Hynek Kydl{\'\i}{\v{c}}ek and Loubna Ben allal and Anton Lozhkov and Margaret Mitchell and Colin Raffel and Leandro Von Werra and Thomas Wolf},
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+ booktitle={The Thirty-eight Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
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+ year={2024},
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+ url={https://openreview.net/forum?id=n6SCkn2QaG}
 
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  }</pre>
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  </d-appendix>
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