Built in visualizers for syntax and NER.Support for custom models in PyTorch, TensorFlow and other frameworks.Easily extensible with custom components and attributes.Components for named entity recognition, part-of-speech-tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking and more.Support for pretrained word vectors and embeddings.Multi-task learning with pretrained transformers like BERT.
We also believe that help is much more valuable if it's shared publicly, so that Please understand that we won't be able to provide individual support via email. The spaCy project is maintained by the spaCy team.
Curious? Fill in our 5-minute questionnaire to tell us what you need and we'll be in touch! Learn more → Services include data strategy, code reviews, pipeline design and annotation coaching. Start by completing our 5-minute questionnaire to tell us what you need and we'll be in touch! Learn more →īespoke advice for problem solving, strategy and analysis for applied NLP projects. Streamlined, production-ready, predictable and maintainable. Get a custom spaCy pipeline, tailor-made for your NLP problem by spaCy's core developers. How to contribute to the spaCy project and code base. Our YouTube channel with video tutorials, talks and more. Learn spaCy in this free and interactive online course. Plugins, extensions, demos and books from the spaCy ecosystem. New features, backwards incompatibilities and migration guide.Įnd-to-end workflows you can clone, modify and run. New to spaCy? Here's everything you need to know! 💫 Version 3.5 out now! Check out the release notes here. 💥 We'd love to hear more about your experience with spaCy! Fill out our survey here. Open-source software, released under the MIT license. Model packaging, deployment and workflow management. Production-ready training system and easy Multi-task learning with pretrained transformers like BERT, as well as a Parsing, named entity recognition, text classification and more, State-of-the-art speed and neural network models for tagging, It's built on the very latest research, and was designed from day one toĬurrently supports tokenization and training for 70+ languages. SpaCy is a library for advanced Natural Language Processing in Python andĬython.
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