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Sockeye is an open-source sequence-to-sequence framework for Neural Machine Translation built on PyTorch. It implements distributed training and optimized inference for state-of-the-art models, powering Amazon Translate and other MT applications. For a quickstart guide to training a standard NMT model on any size of data, see the WMT 2014 English-German tutorial. If you are interested in collaborating or have any questions, please submit a pull request or issue. You can also send questions to sockeye-dev-at-amazon-dot-com. Developers may be interested in our developer guidelines. Starting with version 3.0.0, Sockeye is also based on PyTorch. We maintain backwards compatibility with MXNet models of version 2.3.x with 3.0.x. If MXNet 2.x is installed, Sockeye can run both with PyTorch or MXNet. All models trained with 2.3.x (using MXNet) can be converted to models running with PyTorch using the converter CLI (sockeye.mx_to_pt).
Features
- Sockeye 3 can be installed and run without MXNet
- Sockeye has been used for both academic and industrial research
- Starting with version 3.0.0, Sockeye is also based on PyTorch
- Models trained with PyTorch and Sockeye 3.0.x remain compatible with Sockeye 3.1.x
- All CLIs of Version 3.0.0 now use PyTorch by default
- Implements distributed training and optimized inference for state-of-the-art models
Project Samples
