spaCy/website/docs/models/index.md

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Trained Models & Pipelines	Downloadable trained pipelines and weights for spaCy	Quickstart quickstart Conventions conventions

Quickstart

📖 Installation and usage

For more details on how to use trained pipelines with spaCy, see the usage guide.

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

Package naming 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 is a small English pipeline trained on written web text (blogs, news, comments), that includes vocabulary, vectors, syntax and entities.

Package 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. This is also the source of spaCy's internal compatibility check, performed when you run the download command.