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We introduce PyText - a deep learning based NLP modeling framework built onPyTorch. PyText addresses the often-conflicting requirements of enabling rapidexperimentation and of serving models at scale. It achieves this by providingsimple and extensible interfaces for model components, and by using PyTorch'scapabilities of exporting models for inference via the optimized Caffe2execution engine. We report our own experience of migrating experimentation andproduction workflows to PyText, which enabled us to iterate faster on novelmodeling ideas and then seamlessly ship them at industrial scale.

PyText: A Seamless Path from NLP research to production