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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

, , , , , , , , и . J. Mach. Learn. Res., (2020)

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Approachable Music Composition with Machine Learning at Scale., , , , , , и . ISMIR, стр. 793-800. (2019)A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music., , , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 4361-4370. PMLR, (2018)Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset., , , , , , , , и . CoRR, (2018)MusicLM: Generating Music From Text., , , , , , , , , и 3 other автор(ы). CoRR, (2023)mT5: A massively multilingual pre-trained text-to-text transformer, , , , , , , и . (2020)cite arxiv:2010.11934.How Much Knowledge Can You Pack Into the Parameters of a Language Model?, , и . EMNLP (1), стр. 5418-5426. Association for Computational Linguistics, (2020)NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned., , , , , , , , , и 43 other автор(ы). CoRR, (2021)NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned., , , , , , , , , и 43 other автор(ы). NeurIPS (Competition and Demos), том 133 из Proceedings of Machine Learning Research, стр. 86-111. PMLR, (2020)Counterpoint by Convolution., , , , и . CoRR, (2019)Learning to Groove with Inverse Sequence Transformations., , , , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 2269-2279. PMLR, (2019)