royadityak / 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}, Denny and {Goldie}, Anna and {Luong}, Thang and {Le}, Quoc},
  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,
}

This is not an official Google product.

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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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