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README.md
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README.md
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spaCy is a library for advanced Natural Language Processing in Python and
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Cython. It's built on the very latest research, and was designed from day one to
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be used in real products. spaCy comes with
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[pretrained statistical models](https://spacy.io/models) and word vectors, and
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currently supports tokenization for **60+ languages**. It features
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be used in real products.
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spaCy comes with
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[pretrained pipelines](https://spacy.io/models) and vectors, and
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currently supports tokenization for **59+ languages**. It features
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state-of-the-art speed, convolutional **neural network models** for tagging,
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parsing and **named entity recognition** and easy **deep learning** integration.
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It's commercial open-source software, released under the MIT license.
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parsing, **named entity recognition**, **text classification** and more, multi-task learning with pretrained **transformers** like BERT, as well as a production-ready training system and easy model packaging, deployment and workflow management.
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spaCy is commercial open-source software, released under the MIT license.
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💫 **Version 2.3 out now!**
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[Check out the release notes here.](https://github.com/explosion/spaCy/releases)
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[![Azure Pipelines](<https://img.shields.io/azure-devops/build/explosion-ai/public/8/master.svg?logo=azure-pipelines&style=flat-square&label=build+(3.x)>)](https://dev.azure.com/explosion-ai/public/_build?definitionId=8)
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[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/8/master.svg?logo=azure-pipelines&style=flat-square&label=build)](https://dev.azure.com/explosion-ai/public/_build?definitionId=8)
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[![Current Release Version](https://img.shields.io/github/release/explosion/spacy.svg?style=flat-square&logo=github)](https://github.com/explosion/spaCy/releases)
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[![pypi Version](https://img.shields.io/pypi/v/spacy.svg?style=flat-square&logo=pypi&logoColor=white)](https://pypi.org/project/spacy/)
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[![conda Version](https://img.shields.io/conda/vn/conda-forge/spacy.svg?style=flat-square&logo=conda-forge&logoColor=white)](https://anaconda.org/conda-forge/spacy)
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| --------------- | -------------------------------------------------------------- |
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| [spaCy 101] | New to spaCy? Here's everything you need to know! |
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| [Usage Guides] | How to use spaCy and its features. |
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| [New in v2.3] | New features, backwards incompatibilities and migration guide. |
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| [New in v3.0] | New features, backwards incompatibilities and migration guide. |
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| [API Reference] | The detailed reference for spaCy's API. |
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| [Models] | Download statistical language models for spaCy. |
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| [Universe] | Libraries, extensions, demos, books and courses. |
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| [Contribute] | How to contribute to the spaCy project and code base. |
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[spacy 101]: https://spacy.io/usage/spacy-101
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[new in v2.3]: https://spacy.io/usage/v2-3
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[new in v3.0]: https://spacy.io/usage/v3
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[usage guides]: https://spacy.io/usage/
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[api reference]: https://spacy.io/api/
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[models]: https://spacy.io/models
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much more valuable if it's shared publicly, so that more people can benefit from
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it.
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| Type | Platforms |
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| ------------------------ | ------------------------------------------------------ |
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| 🚨 **Bug Reports** | [GitHub Issue Tracker] |
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| 🎁 **Feature Requests** | [GitHub Issue Tracker] |
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| 👩💻 **Usage Questions** | [Stack Overflow] · [Gitter Chat] · [Reddit User Group] |
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| 🗯 **General Discussion** | [Gitter Chat] · [Reddit User Group] |
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| Type | Platforms |
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| ----------------------- | ---------------------- |
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| 🚨 **Bug Reports** | [GitHub Issue Tracker] |
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| 🎁 **Feature Requests** | [GitHub Issue Tracker] |
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| 👩💻 **Usage Questions** | [Stack Overflow] |
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[github issue tracker]: https://github.com/explosion/spaCy/issues
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[stack overflow]: https://stackoverflow.com/questions/tagged/spacy
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[gitter chat]: https://gitter.im/explosion/spaCy
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[reddit user group]: https://www.reddit.com/r/spacynlp
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## Features
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- Non-destructive **tokenization**
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- **Named entity** recognition
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- Support for **50+ languages**
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- pretrained [statistical models](https://spacy.io/models) and word vectors
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- Support for **59+ languages**
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- **Trained pipelines**
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- Multi-task learning with pretrained **transformers** like BERT
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- Pretrained **word vectors**
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- State-of-the-art speed
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- Easy **deep learning** integration
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- Part-of-speech tagging
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- Labelled dependency parsing
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- Syntax-driven sentence segmentation
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- Production-ready **training system**
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- Linguistically-motivated **tokenization**
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- Components for named **entity recognition**, part-of-speech-tagging, dependency parsing, sentence segmentation, **text classification**, lemmatization, morphological analysis, entity linking and more
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- Easily extensible with **custom components** and attributes
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- Support for custom models in **PyTorch**, **TensorFlow** and other frameworks
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- Built in **visualizers** for syntax and NER
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- Convenient string-to-hash mapping
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- Export to numpy data arrays
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- Efficient binary serialization
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- Easy **model packaging** and deployment
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- Easy **model packaging**, deployment and workflow management
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- Robust, rigorously evaluated accuracy
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📖 **For more details, see the
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[pip]: https://pypi.org/project/spacy/
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[conda]: https://anaconda.org/conda-forge/spacy
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> ⚠️ **Important note for Python 3.8:** We can't yet ship pre-compiled binary
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> wheels for spaCy that work on Python 3.8, as we're still waiting for our CI
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> providers and other tooling to support it. This means that in order to run
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> spaCy on Python 3.8, you'll need [a compiler installed](#source) and compile
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> the library and its Cython dependencies locally. If this is causing problems
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> for you, the easiest solution is to **use Python 3.7** in the meantime.
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### pip
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Using pip, spaCy releases are available as source packages and binary wheels (as
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inputs must match. After updating spaCy, we recommend **retraining your models**
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with the new version.
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📖 **For details on upgrading from spaCy 1.x to spaCy 2.x, see the
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[migration guide](https://spacy.io/usage/v2#migrating).**
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📖 **For details on upgrading from spaCy 2.x to spaCy 3.x, see the
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[migration guide](https://spacy.io/usage/v3#migrating).**
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## Download models
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As of v1.7.0, models for spaCy can be installed as **Python packages**. This
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Trained pipelines for spaCy can be installed as **Python packages**. This
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means that they're a component of your application, just like any other module.
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Models can be installed using spaCy's `download` command, or manually by
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pointing pip to a path or URL.
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| Documentation | |
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| ---------------------- | ------------------------------------------------------------- |
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| [Available Models] | Detailed model descriptions, accuracy figures and benchmarks. |
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| [Models Documentation] | Detailed usage instructions. |
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| Documentation | |
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| ---------------------- | ---------------------------------------------------------------- |
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| [Available Pipelines] | Detailed pipeline descriptions, accuracy figures and benchmarks. |
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| [Models Documentation] | Detailed usage instructions. |
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[available models]: https://spacy.io/models
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[available pipelines]: https://spacy.io/models
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[models documentation]: https://spacy.io/docs/usage/models
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```bash
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# download best-matching version of specific model for your spaCy installation
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# Download best-matching version of specific model for your spaCy installation
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python -m spacy download en_core_web_sm
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# pip install .tar.gz archive from path or URL
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