spaCy
| spaCy | |
|---|---|
 | |
| Original author | Matthew Honnibal |
| Developers | Explosion AI, various |
| Release | February 2015 |
| Stable release | 3.8.4 
/ 14 January 2025 |
| Written in | Python, Cython |
| Operating system | Linux, Windows, macOS, OS X |
| Platform | Cross-platform |
| Type | Natural language processing |
| License | MIT License |
| Website | spacy |
| Repository | |
spaCy (/speɪˈsiː/ spay-SEE) is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.
Unlike NLTK, which is widely used for teaching and research, spaCy focuses on providing software for production usage. spaCy also supports deep learning workflows that allow connecting statistical models trained by popular machine learning libraries like TensorFlow, PyTorch or MXNet through its own machine learning library Thinc. Using Thinc as its backend, spaCy features convolutional neural network models for part-of-speech tagging, dependency parsing, text categorization and named entity recognition (NER). Prebuilt statistical neural network models to perform these tasks are available for 23 languages, including English, Portuguese, Spanish, Russian and Chinese, and there is also a multi-language NER model. Additional support for tokenization for more than 65 languages allows users to train custom models on their own datasets as well.