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70 lines
3.0 KiB
Markdown
70 lines
3.0 KiB
Markdown
---
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title: Trained Models & Pipelines
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teaser: Downloadable trained pipelines and weights for spaCy
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menu:
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- ['Quickstart', 'quickstart']
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- ['Conventions', 'conventions']
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---
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<!-- Update page, refer to new /api/architectures and training docs -->
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This directory includes two types of packages:
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1. **Trained pipelines:** General-purpose spaCy pipelines to predict named
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entities, part-of-speech tags and syntactic dependencies. Can be used
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out-of-the-box and fine-tuned on more specific data.
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2. **Starters:** Transfer learning starter packs with pretrained weights you can
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initialize your pipeline models with to achieve better accuracy. They can
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include word vectors (which will be used as features during training) or
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other pretrained representations like BERT. These packages don't include
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components for specific tasks like NER or text classification and are
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intended to be used as base models when training your own models.
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### Quickstart {hidden="true"}
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import QuickstartModels from 'widgets/quickstart-models.js'
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<QuickstartModels title="Quickstart" id="quickstart" description="Install a default model, get the code to load it from within spaCy and test it." />
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<Infobox title="Installation and usage" emoji="📖">
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For more details on how to use trained pipelines with spaCy, see the
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[usage guide](/usage/models).
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</Infobox>
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## Package naming conventions {#conventions}
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In general, spaCy expects all pipeline packages to follow the naming convention
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of `[lang`\_[name]]. For spaCy's pipelines, we also chose to divide the name
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into three components:
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1. **Type:** Capabilities (e.g. `core` for general-purpose pipeline with
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vocabulary, syntax, entities and word vectors, or `depent` for only vocab,
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syntax and entities).
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2. **Genre:** Type of text the pipeline is trained on, e.g. `web` or `news`.
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3. **Size:** Package size indicator, `sm`, `md` or `lg`.
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For example, [`en_core_web_sm`](/models/en#en_core_web_sm) is a small English
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pipeline trained on written web text (blogs, news, comments), that includes
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vocabulary, vectors, syntax and entities.
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### Package versioning {#model-versioning}
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Additionally, the pipeline package versioning reflects both the compatibility
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with spaCy, as well as the major and minor version. A package version `a.b.c`
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translates to:
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- `a`: **spaCy major version**. For example, `2` for spaCy v2.x.
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- `b`: **Package major version**. Pipelines with a different major version can't
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be loaded by the same code. For example, changing the width of the model,
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adding hidden layers or changing the activation changes the major version.
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- `c`: **Package minor version**. Same pipeline structure, but different
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parameter values, e.g. from being trained on different data, for different
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numbers of iterations, etc.
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For a detailed compatibility overview, see the
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[`compatibility.json`](https://github.com/explosion/spacy-models/tree/master/compatibility.json).
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This is also the source of spaCy's internal compatibility check, performed when
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you run the [`download`](/api/cli#download) command.
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