This portal provides an advanced documentation of the OpenNMT Torch version.


OpenNMT is a generic deep learning framework mainly specialized in sequence-to-sequence models covering a variety of tasks such as machine translation, summarization, image to text, and speech recognition. The framework has also been extended for other non sequence-to-sequence tasks like language modelling and sequence tagging.

All these applications are reusing and sometimes extending a collection of easy-to-reuse modules: encoders, decoders, embeddings layers, attention layers, and more.

The framework is implemented to be as generic as possible and can be used either via command line applications, client-server, or libraries.

Additional resources

You can find additional help or tutorials in the following resources:


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