https://github.com/nrc-cnrc/sockeye-multisource

Multi-source version of the Sockeye sequence-to-sequence framework for Neural Machine Translation — Version multi-source de Sockeye, le cadre séquence-à-séquence pour la traduction automatique neuronale
https://github.com/nrc-cnrc/sockeye-multisource

nmt sockeye transformer

Last synced: 3 months ago
JSON representation

Multi-source version of the Sockeye sequence-to-sequence framework for Neural Machine Translation — Version multi-source de Sockeye, le cadre séquence-à-séquence pour la traduction automatique neuronale

• Host: GitHub
• URL: https://github.com/nrc-cnrc/sockeye-multisource
• Owner: nrc-cnrc
• License: apache-2.0
• Created: 2019-07-04T17:19:45.000Z (almost 6 years ago)
• Default Branch: multisource.enc_attn
• Last Pushed: 2024-07-10T12:49:21.000Z (11 months ago)
• Last Synced: 2025-01-14T04:12:29.744Z (5 months ago)
• Topics: nmt, sockeye, transformer
• Language: Python
• Homepage:
• Size: 2.98 MB
• Stars: 1
• Watchers: 7
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Codeowners: .github/CODEOWNERS

Awesome Lists containing this project

README

        
# Sockeye

[![PyPI version](https://badge.fury.io/py/sockeye.svg)](https://badge.fury.io/py/sockeye)

[![GitHub license](https://img.shields.io/github/license/awslabs/sockeye.svg)](https://github.com/awslabs/sockeye/blob/master/LICENSE)

[![GitHub issues](https://img.shields.io/github/issues/awslabs/sockeye.svg)](https://github.com/awslabs/sockeye/issues)

[![Build Status](https://travis-ci.org/awslabs/sockeye.svg?branch=master)](https://travis-ci.org/awslabs/sockeye)

[![Documentation Status](https://readthedocs.org/projects/sockeye/badge/?version=latest)](http://sockeye.readthedocs.io/en/latest/?badge=latest)

This package contains the Sockeye project, a sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet (Incubating).

It implements state-of-the-art encoder-decoder architectures, such as:

- Deep Recurrent Neural Networks with Attention [[Bahdanau, '14](https://arxiv.org/abs/1409.0473)]

- Transformer Models with self-attention [[Vaswani et al, '17](https://arxiv.org/abs/1706.03762)]

- Fully convolutional sequence-to-sequence models [[Gehring et al, '17](https://arxiv.org/abs/1705.03122)]

In addition, it provides an experimental [image-to-description module](https://github.com/awslabs/sockeye/tree/master/sockeye/image_captioning) that can be used for image captioning.

Recent developments and changes are tracked in our [CHANGELOG](https://github.com/awslabs/sockeye/blob/master/CHANGELOG.md).

If you have any questions or discover problems, please [file an issue](https://github.com/awslabs/sockeye/issues/new).

You can also send questions to *sockeye-dev-at-amazon-dot-com*.

## Documentation

For information on how to use Sockeye, please visit [our documentation](https://awslabs.github.io/sockeye/).

Developers may be interested in our [developer guidelines](https://awslabs.github.io/sockeye/development.html).

## Citation

For technical information about Sockeye, see our paper on the arXiv ([BibTeX](sockeye.bib)):

> Felix Hieber, Tobias Domhan, Michael Denkowski, David Vilar, Artem Sokolov, Ann Clifton and Matt Post. 2017.

> [Sockeye: A Toolkit for Neural Machine Translation](https://arxiv.org/abs/1712.05690). ArXiv e-prints.