<a href="https://explosion.ai"><img src="https://explosion.ai/assets/img/logo.svg" width="125" height="125" align="right" /></a>
# 💫 🤖 spaCy Curated Transformers
This package provides [spaCy](https://github.com/explosion/spaCy) components and
architectures to use a curated set of transformer models via
[`curated-transformers`](https://github.com/explosion/curated-transformers) in
spaCy.
[](https://pypi.python.org/pypi/spacy-curated-transformers)
[](https://github.com/explosion/spacy-curated-transformers/releases)
## Features
- Use pretrained models based on one of the following architectures to
power your spaCy pipeline:
- ALBERT
- BERT
- CamemBERT
- RoBERTa
- XLM-RoBERTa
- All the nice features supported by [`spacy-transformers`](https://github.com/explosion/spacy-transformers)
such as support for Hugging Face Hub, **multi-task learning**, the extensible config system and
out-of-the-box serialization
- Deep integration into spaCy, which lays the groundwork for deployment-focused features
such as distillation and quantization
- Minimal dependencies
## ⏳ Installation
Installing the package from pip will automatically install all dependencies.
```bash
pip install spacy-curated-transformers
```
## 🚀 Quickstart
An example project is provided in the [`project`](project) directory.
## 📖 Documentation
- 📘
[Layers and Model Architectures](https://spacy.io/usage/layers-architectures):
Power spaCy components with custom neural networks
- 📗 [`CuratedTransformer`](https://spacy.io/api/curatedtransformer): Pipeline component API
reference
- 📗
[Transformer architectures](https://spacy.io/api/architectures#curated-trf):
Architectures and registered functions
## Bug reports and other issues
Please use [spaCy's issue tracker](https://github.com/explosion/spaCy/issues) to
report a bug, or open a new thread on the
[discussion board](https://github.com/explosion/spaCy/discussions) for any other
issue.
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"description": "<a href=\"https://explosion.ai\"><img src=\"https://explosion.ai/assets/img/logo.svg\" width=\"125\" height=\"125\" align=\"right\" /></a>\n\n# \ud83d\udcab \ud83e\udd16 spaCy Curated Transformers\n\nThis package provides [spaCy](https://github.com/explosion/spaCy) components and\narchitectures to use a curated set of transformer models via\n[`curated-transformers`](https://github.com/explosion/curated-transformers) in\nspaCy.\n\n[](https://pypi.python.org/pypi/spacy-curated-transformers)\n[](https://github.com/explosion/spacy-curated-transformers/releases)\n\n## Features\n\n- Use pretrained models based on one of the following architectures to\n power your spaCy pipeline:\n - ALBERT\n - BERT\n - CamemBERT\n - RoBERTa\n - XLM-RoBERTa\n- All the nice features supported by [`spacy-transformers`](https://github.com/explosion/spacy-transformers)\n such as support for Hugging Face Hub, **multi-task learning**, the extensible config system and\n out-of-the-box serialization\n- Deep integration into spaCy, which lays the groundwork for deployment-focused features\n such as distillation and quantization\n- Minimal dependencies\n\n## \u23f3 Installation\n\nInstalling the package from pip will automatically install all dependencies.\n\n```bash\npip install spacy-curated-transformers\n```\n\n## \ud83d\ude80 Quickstart\n\nAn example project is provided in the [`project`](project) directory.\n\n## \ud83d\udcd6 Documentation\n\n- \ud83d\udcd8\n [Layers and Model Architectures](https://spacy.io/usage/layers-architectures):\n Power spaCy components with custom neural networks\n- \ud83d\udcd7 [`CuratedTransformer`](https://spacy.io/api/curatedtransformer): Pipeline component API\n reference\n- \ud83d\udcd7\n [Transformer architectures](https://spacy.io/api/architectures#curated-trf):\n Architectures and registered functions\n\n## Bug reports and other issues\n\nPlease use [spaCy's issue tracker](https://github.com/explosion/spaCy/issues) to\nreport a bug, or open a new thread on the\n[discussion board](https://github.com/explosion/spaCy/discussions) for any other\nissue.\n",
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