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Title: GitHub - lipond/tensor2tensor: Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. · GitHub

Open Graph Title: GitHub - lipond/tensor2tensor: Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

X Title: GitHub - lipond/tensor2tensor: Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Description: Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. - lipond/tensor2tensor

Open Graph Description: Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. - lipond/tensor2tensor

X Description: Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. - lipond/tensor2tensor

Opengraph URL: https://github.com/lipond/tensor2tensor

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	https://floydhub.com/run
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T2T	https://github.com/tensorflow/tensor2tensor
accelerate ML research	https://research.googleblog.com/2017/06/accelerating-deep-learning-research.html
Google Brain team	https://research.google.com/teams/brain/
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	https://github.com/lipond/tensor2tensor#quick-start
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	https://github.com/lipond/tensor2tensor#contents
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Attention Is All You Need	https://arxiv.org/abs/1706.03762
	https://github.com/lipond/tensor2tensor#installation
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	https://github.com/lipond/tensor2tensor#papers
this paper	https://arxiv.org/abs/1803.07416
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Attention Is All You Need	https://arxiv.org/abs/1706.03762
Depthwise Separable Convolutions for Neural Machine Translation	https://arxiv.org/abs/1706.03059
One Model To Learn Them All	https://arxiv.org/abs/1706.05137
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Generating Wikipedia by Summarizing Long Sequences	https://arxiv.org/abs/1801.10198
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Training Tips for the Transformer Model	https://arxiv.org/abs/1804.00247
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Fast Decoding in Sequence Models using Discrete Latent Variables	https://arxiv.org/abs/1803.03382
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost	https://arxiv.org/abs/1804.04235
Universal Transformers	https://arxiv.org/abs/1807.03819
Readme	https://github.com/lipond/tensor2tensor#readme-ov-file
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