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This is an earlier version of OpenNMT used for training, tuning, and testing the core models with diffs in the paper "Adapting Sequence Models for Sentence Correction", EMNLP 2017.

Note that an option -tag_weight for translate.lua allows an additive weight to be applied to the four diff tags.

OpenNMT: Open-Source Neural Machine Translation

The most recent version and documentation for OpenNMT is available here: https://github.com/opennmt/opennmt

Installation

OpenNMT only requires a vanilla Torch install with few dependencies.

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

  1. Train the model.

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

  1. Translate sentences.

th translate.lua -model model_final.t7 -src data/src-test.txt -tag_weight 0.0 -output pred.txt

OpenNMT 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} }