Update v2.2 page [ci skip]

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Ines Montani 2019-10-01 14:11:05 +02:00
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commit 66aa0d479f
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spaCy v2.2 features improved statistical models, new pretrained models for
Norwegian and Lithuanian, better Dutch NER, as well as a new mechanism for
storing language data that makes the installation about **7× smaller** on
disk. We've also added a new class to efficiently **serialize annotations**, an
improved and **10× faster** phrase matching engine, built-in scoring and
**CLI training for text classification**, a new command to analyze and **debug
training data**, data augmentation during training and more. For the full
changelog, see the
storing language data that makes the installation about **5-10× smaller**
on disk. We've also added a new class to efficiently **serialize annotations**,
an improved and **10× faster** phrase matching engine, built-in scoring
and **CLI training for text classification**, a new command to analyze and
**debug training data**, data augmentation during training and more. For the
full changelog, see the
[release notes on GitHub](https://github.com/explosion/spaCy/releases/tag/v2.2.0).
<!-- For more details and a behind-the-scenes look at the new release,
@ -127,10 +127,10 @@ checks. They're also fully serializable out-of-the-box. All large data resources
like lemmatization tables have been moved to a separate package,
[`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data) that can
be installed alongside the core library. This allowed us to make the spaCy
installation roughly **7&times; smaller on disk**. [Pretrained models](/models)
now include their data files, so you only need to install the lookups if you
want to build blank models or use lemmatization with languages that don't yet
ship with pretrained models.
installation **5-10&times; smaller on disk** (depending on your platform).
[Pretrained models](/models) now include their data files, so you only need to
install the lookups if you want to build blank models or use lemmatization with
languages that don't yet ship with pretrained models.
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