Hi all, I'm one of the original authors of OpenNMT and an nlp prof, always nice to see it trending :). I work with Hugging Face (https://huggingface.co/) now, we do similar things for NLP generally as well as supporting NMT applications.
I noticed that your swift libraries will be ready so that refined attention based models can be put on device for iOS . Will you also support android also ?
Looks cool, but it hasn't been updated in a bit and as they note, the Torch framework is no longer maintained. There is a PyTorch alternative that appears more active: https://github.com/OpenNMT/OpenNMT-py.
As someone who has work with all three NLP toolkit: huggingface, openmt-py and fairseq. I always have trouble juggling through the heavy abstraction of openmt-py.
For example in openmt-py you need to write fields, reader and raw datasets before you even load into their complex dataset class. Each item is heavily abstracted through several layers of classes. I understand this improve code reuse, but introduce a huge steep curve for newcomer.
Huggingface approach on the other hand is slightly more "messy" [2] but easier to understand and add your own tweak.
Main Versions (supported by folks at systran): https://github.com/OpenNMT/OpenNMT-tf https://github.com/opennmt/opennmt-py
Happy to answer any questions about NLP, neural models, open-source ML.