Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/google/seq2seq

A general-purpose encoder-decoder framework for Tensorflow
https://github.com/google/seq2seq

deeplearning machine-translation neural-network tensorflow translation

Last synced: about 1 month ago
JSON representation

A general-purpose encoder-decoder framework for Tensorflow

Awesome Lists containing this project

README

        

[![CircleCI](https://circleci.com/gh/google/seq2seq.svg?style=svg)](https://circleci.com/gh/google/seq2seq)

---

**[READ THE DOCUMENTATION](https://google.github.io/seq2seq)**

**[CONTRIBUTING](https://google.github.io/seq2seq/contributing/)**

---

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](https://3.bp.blogspot.com/-3Pbj_dvt0Vo/V-qe-Nl6P5I/AAAAAAAABQc/z0_6WtVWtvARtMk0i9_AtLeyyGyV6AI4wCLcB/s1600/nmt-model-fast.gif)

---

The official code used for the [Massive Exploration of Neural Machine Translation Architectures](https://arxiv.org/abs/1703.03906) 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.