spaCy/website/docs/models/index.md

---
title: Trained Models & Pipelines
teaser: Downloadable trained pipelines and weights for spaCy
menu:
  - ['Quickstart', 'quickstart']
  - ['Conventions', 'conventions']
---

<!-- Update page, refer to new /api/architectures and training docs -->

This directory includes two types of packages:

1. **Trained pipelines:** General-purpose spaCy pipelines to predict named
   entities, part-of-speech tags and syntactic dependencies. Can be used
   out-of-the-box and fine-tuned on more specific data.
2. **Starters:** Transfer learning starter packs with pretrained weights you can
   initialize your pipeline models with to achieve better accuracy. They can
   include word vectors (which will be used as features during training) or
   other pretrained representations like BERT. These packages don't include
   components for specific tasks like NER or text classification and are
   intended to be used as base models when training your own models.

### Quickstart {hidden="true"}

import QuickstartModels from 'widgets/quickstart-models.js'

<QuickstartModels title="Quickstart" id="quickstart" description="Install a default model, get the code to load it from within spaCy and test it." />

<Infobox title="Installation and usage" emoji="📖">

For more details on how to use trained pipelines with spaCy, see the
[usage guide](/usage/models).

</Infobox>

## Package naming conventions {#conventions}

In general, spaCy expects all pipeline packages to follow the naming convention
of `[lang`\_[name]]. For spaCy's pipelines, we also chose to divide the name
into three components:

1. **Type:** Capabilities (e.g. `core` for general-purpose pipeline with
   vocabulary, syntax, entities and word vectors, or `depent` for only vocab,
   syntax and entities).
2. **Genre:** Type of text the pipeline is trained on, e.g. `web` or `news`.
3. **Size:** Package size indicator, `sm`, `md` or `lg`.

For example, [`en_core_web_sm`](/models/en#en_core_web_sm) is a small English
pipeline trained on written web text (blogs, news, comments), that includes
vocabulary, vectors, syntax and entities.

### Package versioning {#model-versioning}

Additionally, the pipeline package versioning reflects both the compatibility
with spaCy, as well as the major and minor version. A package version `a.b.c`
translates to:

- `a`: **spaCy major version**. For example, `2` for spaCy v2.x.
- `b`: **Package major version**. Pipelines with a different major version can't
  be loaded by the same code. For example, changing the width of the model,
  adding hidden layers or changing the activation changes the major version.
- `c`: **Package minor version**. Same pipeline structure, but different
  parameter values, e.g. from being trained on different data, for different
  numbers of iterations, etc.

For a detailed compatibility overview, see the
[`compatibility.json`](https://github.com/explosion/spacy-models/tree/master/compatibility.json).
This is also the source of spaCy's internal compatibility check, performed when
you run the [`download`](/api/cli#download) command.