# seq2seq

**Repository Path**: deeplearningrepos/seq2seq

## Basic Information

- **Project Name**: seq2seq
- **Description**: A general-purpose encoder-decoder framework for Tensorflow
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-03-30
- **Last Updated**: 2021-08-31

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## 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.