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💫 Models for the spaCy Natural Language Processing (NLP) library
| Date | Stars |
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| 2026-07-24 | 1894 |
| 2026-07-25 | 1894 |
| 2026-07-28 | 1894 |
| 2026-07-30 | 1894 |
| 2026-08-06 | 1894 |
Today
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growth rate 0.00%/day
<a href="https://explosion.ai"><img src="https://explosion.ai/assets/img/logo.svg" width="125" height="125" align="right" /></a>
# spaCy models
This repository contains
[releases](https://github.com/explosion/spacy-models/releases) of models for
the [spaCy](https://github.com/explosion/spaCy) NLP library. For more info on
how to download, install and use the models, see the [models
documentation](https://spacy.io/usage/models).
> **⚠️ Important note:** Because the models can be very large and consist mostly
> of binary data, we can't simply provide them as files in a GitHub repository.
> Instead, we've opted for adding them to
> [releases](https://github.com/explosion/spacy-models/releases) as `.whl` and
> `.tar.gz` files. This allows us to still maintain a public release history.
## Quickstart
To install a specific model, run the following command with the model name (for
example `en_core_web_sm`):
```bash
python -m spacy download [model]
```
- [spaCy v3.x models directory](https://spacy.io/models)
- [spaCy v3.x model comparison](https://spacy.io/usage/facts-figures#spacy-models)
- [spaCy v2.x models directory](https://v2.spacy.io/models)
- [spaCy v2.x model comparison](https://v2.spacy.io/usage/facts-figures#spacy-models)
- [Individual release notes](https://github.com/explosion/spacy-models/releases)
For the spaCy v1.x models, [see here](#spacy-v1x-releases).
## Model naming conventions
In general, spaCy expects all model packages to follow the naming convention of
`[lang]_[name]`. For our provided pipelines, we divide the name into three
components:
- **type**: Model capabilities:
- `core`: a general-purpose model with tagging, parsing, lemmatization and
named entity recognition
- `dep`: only tagging, parsing and lemmatization
- `ent`: only named entity recognition
- `sent`: only sentence segmentation
- **genre**: Type of text the model is trained on (e.g. `web` for web text,
`news` for news text)
- **size**: Model size indicator:
- `sm`: no word vectors
- `md`: reduced word vector table with 20k unique vectors for ~500k words
- `lg`: large word vector table with ~500k entries
For example, `en_core_web_md` is a medium-sized English model trained on
written web text (blogs, news, comments), that includes a tagger, a dependency
parser, a lemmatizer, a named entity recognizer and a word vector table with
20k unique vectors.
### Model versioning
Additionally, the model versioning reflects both the compatibility with spaCy,
as well as the model version. A model version `a.b.c` translates to:
- `a`: **spaCy major version**. For example, `2` for spaCy v2.x.
- `b`: **spaCy minor version**. For example, `3` for spaCy v2.3.x.
- `c`: **Model version.** Different model config: e.g. from being trained on
different data, with different parameters, for different numbers of
iterations, with different vectors, etc.
For a detailed compatibility overview, see the
[`compatibility.json`](compatibility.json). This is also the source of spaCy's
internal compatibility check, performed when you run the `download` command.
### Support for older versions
If you're using an older version (v1.6.0 or below), you can still download and
install the old models from within spaCy using `python -m spacy.en.download all`
or `python -m spacy.de.download all`. The `.tar.gz` archives are also
[attached to the v1.6.0 release](https://github.com/explosion/spaCy/tree/v1.6.0).
To download and install the models manually, unpack the archive, drop the
contained directory into `spacy/data` and load the model via `spacy.load('en')`
or `spacy.load('de')`.
## Downloading models
To increase transparency and make it easier to use spaCy with your own models,
all data is now available as direct downloads, organised in
[individual releases](https://github.com/explosion/spacy-models/releases). spaCy
1.7 also supports installing and loading models as **Python packages**. You can
now choose how and where you want to keep the data files,Excerpt of 11,494 characters
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Explosion Bot · @explosion
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Adriane Boyd
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Ines Montani · Founder @explosion · Germany
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Matthew Honnibal · Founder @explosion · Germany
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Paul O'Leary McCann · Cotonoha · Japan
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:b035f0d1f94f2444, topic:nlp, topic:natural-language-processing, topic:spacy