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

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

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

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

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

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LICENSE	https://github.com/GeorgiBalb/tensor2tensor-fork/blob/master/LICENSE
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	https://github.com/GeorgiBalb/tensor2tensor-fork#tensor2tensor
	https://badge.fury.io/py/tensor2tensor
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accelerate ML research	https://research.googleblog.com/2017/06/accelerating-deep-learning-research.html
Google Brain team	https://research.google.com/teams/brain/
Trax	https://github.com/google/trax
	https://github.com/GeorgiBalb/tensor2tensor-fork#quick-start
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	https://github.com/GeorgiBalb/tensor2tensor-fork#contents
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Mathematical Language Understanding	https://github.com/GeorgiBalb/tensor2tensor-fork#mathematical-language-understanding
Story, Question and Answer	https://github.com/GeorgiBalb/tensor2tensor-fork#story-question-and-answer
Image Classification	https://github.com/GeorgiBalb/tensor2tensor-fork#image-classification
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Language Modeling	https://github.com/GeorgiBalb/tensor2tensor-fork#language-modeling
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Speech Recognition	https://github.com/GeorgiBalb/tensor2tensor-fork#speech-recognition
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Translation	https://github.com/GeorgiBalb/tensor2tensor-fork#translation
Basics	https://github.com/GeorgiBalb/tensor2tensor-fork#basics
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	https://github.com/GeorgiBalb/tensor2tensor-fork#story-question-and-answer
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example	https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/notebooks/Transformer_translate.ipynb
	https://github.com/GeorgiBalb/tensor2tensor-fork#basics
	https://github.com/GeorgiBalb/tensor2tensor-fork#walkthrough
Attention Is All You Need	https://arxiv.org/abs/1706.03762
	https://github.com/GeorgiBalb/tensor2tensor-fork#installation
	https://github.com/GeorgiBalb/tensor2tensor-fork#features
distributed training	https://tensorflow.github.io/tensor2tensor/distributed_training.html
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	https://github.com/GeorgiBalb/tensor2tensor-fork#t2t-overview
	https://github.com/GeorgiBalb/tensor2tensor-fork#problems
all_problems.py	https://github.com/tensorflow/tensor2tensor/tree/master/tensor2tensor/data_generators/all_problems.py
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	https://github.com/GeorgiBalb/tensor2tensor-fork#models
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	https://github.com/GeorgiBalb/tensor2tensor-fork#trainer
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	https://github.com/GeorgiBalb/tensor2tensor-fork#adding-your-own-components
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	https://github.com/GeorgiBalb/tensor2tensor-fork#adding-a-dataset
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data generators README	https://github.com/tensorflow/tensor2tensor/tree/master/tensor2tensor/data_generators/README.md
	https://github.com/GeorgiBalb/tensor2tensor-fork#run-on-floydhub
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Terms of Service	https://www.floydhub.com/about/terms
	https://github.com/GeorgiBalb/tensor2tensor-fork#papers
this paper	https://arxiv.org/abs/1803.07416
Google Research Blog post introducing T2T	https://research.googleblog.com/2017/06/accelerating-deep-learning-research.html
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
Discrete Autoencoders for Sequence Models	https://arxiv.org/abs/1801.09797
Generating Wikipedia by Summarizing Long Sequences	https://arxiv.org/abs/1801.10198
Image Transformer	https://arxiv.org/abs/1802.05751
Training Tips for the Transformer Model	https://arxiv.org/abs/1804.00247
Self-Attention with Relative Position Representations	https://arxiv.org/abs/1803.02155
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
Attending to Mathematical Language with Transformers	https://arxiv.org/abs/1812.02825
The Evolved Transformer	https://arxiv.org/abs/1901.11117
Model-Based Reinforcement Learning for Atari	https://arxiv.org/abs/1903.00374
VideoFlow: A Flow-Based Generative Model for Video	https://arxiv.org/abs/1903.01434
Readme	https://github.com/GeorgiBalb/tensor2tensor-fork#readme-ov-file
Apache-2.0 license	https://github.com/GeorgiBalb/tensor2tensor-fork#Apache-2.0-1-ov-file
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