Examples, tutorials and use cases for the Marian toolkit.
More information on https://marian-nmt.github.io
List of examples:
translating-amun-- examples for translating with Amun
training-basics-- the complete example for training a WMT16-scale model
training-basics, but uses built-in SentencePiece for data processing, requires Marian v1.7+
transformer-- scripts for training the transformer model
wmt2017-uedin-- scripts for building a WMT2017-grade model for en-de based on Edinburgh's WMT2017 submission
wmt2017-transformer-- scripts for building a better than WMT2017-grade model for en-de, beating WMT2017 submission by 1.2 BLEU
First download common tools:
cd tools make all cd ..
Next, go to the chosen directory and run
cd training-basics ./run-me.sh
The README file in each directory provides more detailed description.
The development of Marian received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreements 688139 (SUMMA; 2016-2019), 645487 (Modern MT; 2015-2017), 644333 (TraMOOC; 2015-2017), 644402 (HiML; 2015-2017), the Amazon Academic Research Awards program, and the World Intellectual Property Organization.
This software contains source code provided by NVIDIA Corporation.