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Author
Project Page
http://opennmt.net/
Last Commit
Feb. 21, 2017
Created
Oct. 24, 2016

Build Status

OpenNMT: Open-Source Neural Machine Translation

OpenNMT is a full-featured, open-source (MIT) neural machine translation system utilizing the Torch mathematical toolkit.

The system is designed to be simple to use and easy to extend , while maintaining efficiency and state-of-the-art translation accuracy. Features include:

  • Speed and memory optimizations for high-performance GPU training.
  • Simple general-purpose interface, only requires and source/target data files.
  • C++ implementation of the translator for easy deployment.
  • Extensions to allow other sequence generation tasks such as summarization and image captioning.

Installation

OpenNMT only requires a vanilla Torch install with few dependencies. Alternatively there is a (CUDA) Docker container.

Dependencies

  • nn
  • nngraph
  • tds
  • penlight

GPU training requires:

  • cunn
  • cutorch

Multi-GPU training additionally requires:

  • threads

Quickstart

OpenNMT consists of three commands:

1) Preprocess the data.

th preprocess.lua -train_src data/src-train.txt -train_tgt data/tgt-train.txt -valid_src data/src-val.txt -valid_tgt data/tgt-val.txt -save_data data/demo

2) Train the model.

th train.lua -data data/demo-train.t7 -save_model model

3) Translate sentences.

th translate.lua -model model_final.t7 -src data/src-test.txt -output pred.txt

See the guide for more details.

Citation

A technical report on OpenNMT is available. If you use the system for academic work, please cite:

    @ARTICLE{2017opennmt,
         author = { {Klein}, G. and {Kim}, Y. and {Deng}, Y. 
                    and {Senellart}, J. and {Rush}, A.~M.},
         title = "{OpenNMT: Open-Source Toolkit 
                   for Neural Machine Translation}",
         journal = {ArXiv e-prints},
         eprint = {1701.02810} }

Documentation

Latest Releases
v0.4.1
 Feb. 16 2017
v0.4.0
 Feb. 10 2017
v0.3.0
 Jan. 23 2017
v0.2.0
 Jan. 2 2017
v0.1.0
 Dec. 19 2016