We describe an open-source toolkit for neural machine translation (NMT). The toolkit prioritizes efficiency, modularity, and extensibility with the goal of supporting NMT research into model architectures, feature representations, and source modalities, while maintaining competitive performance and reasonable training requirements. The toolkit consists of modeling and translation support, as well as detailed pedagogical documentation about the underlying techniques.
@article{arxiv.1701.02810,
title = {OpenNMT: Open-Source Toolkit for Neural Machine Translation},
author = {Guillaume Klein and Yoon Kim and Yuntian Deng and Jean Senellart and Alexander M. Rush},
journal= {arXiv preprint arXiv:1701.02810},
year = {2017}
}