spaCy is designed to help you do real work, to build real products, or gather real insights. The library respects your time, and tries to avoid wasting it. It's easy to install, and its API is simple and productive. spaCy excels at large-scale information extraction tasks. It's written from the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. Since its release in 2015, spaCy has become an industry standard with a huge ecosystem. Choose from a variety of plugins, integrate with your machine learning stack and build custom components and workflows.
Features
- Support for 75+ languages
- 84 trained pipelines for 25 languages
- Components for named entity recognition, part-of-speech tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking and more
- Multi-task learning with pretrained transformers like BERT
- Pretrained word vectors
- Production-ready training system
- Linguistically-motivated tokenization
- Easily extensible with custom components and attributes
Project Samples
Categories
Machine LearningLicense
MIT LicenseFollow spaCy models
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