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Recent work has demonstrated that increased training dataset diversity improves general cross-domain knowledge and downstream generalization capability for large-scale language models. With this in mind, we present \textit{the Pile}: an 825 GiB English text corpus targeted at training large-scale language models. The Pile is constructed from 22 diverse high-quality subsets -- both existing and newly constructed -- many of which derive from academic or professional sources. Our evaluation of the untuned performance of GPT-2 and GPT-3 on the Pile shows that these models struggle on many of its components, such as academic writing. Conversely, models trained on the Pile improve significantly over both Raw CC and CC-100 on all components of the Pile, while improving performance on downstream evaluations. Through an in-depth exploratory analysis, we document potentially concerning aspects of the data for prospective users. We make publicly available the code used in its construction.🗓️ Mark your calendar from September 20, 2024 to September 21, 2024 at Subterranean. Pile is a celebration of passion, innovation, and community. Embrace the opportunity to explore the world of Rock in a dynamic setting in Illinois, United States. Reserve your spot now for tickets starting at just 35.00 USD 🎟️.
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Subterranean, 2011 North Ave, Chicago, IL 60647, United States
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