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OpenNMT is an open source ecosystem for neural machine translation and neural sequence learning.

Started in December 2016 by the Harvard NLP group and SYSTRAN, the project has since been used in several research and industry applications. It is currently maintained by SYSTRAN and Ubiqus.

OpenNMT provides implementations in 2 popular deep learning frameworks:

OpenNMT-py

User-friendly and multimodal, benefiting from PyTorch ease of use.

• Documentation
• Pretrained models

OpenNMT-tf

Modular and stable, powered by the TensorFlow ecosystem.

• Documentation
• Pretrained models

Each implementation has its own set of unique features but shares similar goals:

• Highly configurable model architectures and training procedures
• Efficient model serving capabilities for use in real world applications
• Extensions to allow other tasks such as text generation, tagging, summarization, image to text, and speech to text

The OpenNMT ecosystem also includes projects to cover the full NMT workflow:

CTranslate2

Efficient inference engine for Transformer models on CPU and GPU.

• Documentation

Tokenizer

Fast and customizable text tokenization library with BPE and SentencePiece support.

• Documentation