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eXtensible Neural Machine Translation
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eXtensible Neural Machine Translation

This is a repository for the extensible neural machine translation toolkit xnmt. The over-arching goal of xnmt is that it be easy to use for research, and thus it supports a modular design that means that new methods should be easy to implement by adding new modules. It is coded in Python based on DyNet.

More information can be found in the documentation.

If you use xnmt in a research paper, we'd appreciate if you cite the following system description:

    title = {{XNMT}: The eXtensible Neural Machine Translation Toolkit},
    author = {Graham Neubig and Matthias Sperber and Xinyi Wang and Matthieu Felix and Austin Matthews and Sarguna Padmanabhan and Ye Qi and Devendra Singh Sachan and Philip Arthur and Pierre Godard and John Hewitt and Rachid Riad and Liming Wang },
    booktitle = {Conference of the Association for Machine Translation in the Americas (AMTA) Open Source Software Showcase},
    address = {Boston},
    month = {March},
    year = {2018}

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