spaCy/website/docs/models/index.md

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

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

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

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

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.