mirror of https://github.com/explosion/spaCy.git
70 lines
3.0 KiB
Markdown
70 lines
3.0 KiB
Markdown
---
|
|
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.
|