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GSPMD: General and Scalable Parallelization for ML Computation Graphs., , , , , , , , , and 6 other author(s). CoRR, (2021)Mesh-tensorflow: Deep learning for supercomputers, , , , , , , , , and 1 other author(s). Advances in Neural Information Processing Systems, page 10435--10444. (2018)Adafactor: Adaptive Learning Rates with Sublinear Memory Cost., and . ICML, volume 80 of Proceedings of Machine Learning Research, page 4603-4611. PMLR, (2018)Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer, , , , , , , , and . (October 2019)cite arxiv:1910.10683.Searching for Efficient Transformers for Language Modeling., , , , , and . NeurIPS, page 6010-6022. (2021)Blockwise Parallel Decoding for Deep Autoregressive Models., , and . NeurIPS, page 10107-10116. (2018)Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity., , and . J. Mach. Learn. Res., (2022)Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer., , , , , , , , and . J. Mach. Learn. Res., (2020)Music Transformer: Generating Music with Long-Term Structure, , , , , , , , , and . 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, OpenReview.net, (2019)GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding., , , , , , , , and . ICLR, OpenReview.net, (2021)