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Ines Montani 2019-03-23 16:46:34 +01:00
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@ -95,6 +95,21 @@ systems, or to pre-process text for **deep learning**.
publishing spaCy and other software is called
[Explosion AI](https://explosion.ai).
<Infobox title="Download the spaCy Cheat Sheet!">
[![spaCy Cheatsheet](../images/cheatsheet.jpg)](http://datacamp-community-prod.s3.amazonaws.com/29aa28bf-570a-4965-8f54-d6a541ae4e06)
For the launch of our
["Advanced NLP with spaCy"](https://www.datacamp.com/courses/advanced-nlp-with-spacy)
course on DataCamp we created the first official spaCy cheat sheet! A handy
two-page reference to the most important concepts and features, from loading
models and accessing linguistic annotations, to custom pipeline components and
rule-based matching.
<p><Button to="http://datacamp-community-prod.s3.amazonaws.com/29aa28bf-570a-4965-8f54-d6a541ae4e06" variant="primary">Download</Button></p>
</Infobox>
## Features {#features}
In the documentation, you'll come across mentions of spaCy's features and

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@ -13,6 +13,8 @@ design changes introduced in [v2.0](/usage/v2). As well as smaller models,
faster runtime, and many bug fixes, v2.1 also introduces experimental support
for some exciting new NLP innovations. For the full changelog, see the
[release notes on GitHub](https://github.com/explosion/spaCy/releases/tag/v2.1.0).
For more details and a behind-the-scenes look at the new release,
[see our blog post](https://explosion.ai/blog/spacy-v2-1).
### BERT/ULMFit/Elmo-style pre-training {#pretraining tag="experimental"}