vtpp2014 / seq2seq

A general-purpose encoder-decoder framework for Tensorflow

Home Page:https://google.github.io/seq2seq/

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A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more.

Translation Model


The official code used for the Massive Exploration of Neural Machine Translation Architectures paper.

If you use this code for academic purposes, please cite it as:

@ARTICLE{Britz:2017,
  author          = {{Britz}, D. and {Goldie}, A. and {Luong}, T. and {Le}, Q.},
  title           = "{Massive Exploration of Neural Machine Translation Architectures}",
  journal         = {ArXiv e-prints},
  archivePrefix   = "arXiv",
  eprinttype      = {arxiv},
  eprint          = {1703.03906},
  primaryClass    = "cs.CL",
  keywords        = {Computer Science - Computation and Language},
  year            = 2017,
  month           = mar,
}

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A general-purpose encoder-decoder framework for Tensorflow

https://google.github.io/seq2seq/

License:Apache License 2.0


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