mirror of https://github.com/explosion/spaCy.git
71 lines
3.0 KiB
Markdown
71 lines
3.0 KiB
Markdown
---
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title: Models
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teaser: Downloadable pretrained models 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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The models directory includes two types of pretrained models:
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1. **Core models:** General-purpose pretrained models to predict named entities,
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part-of-speech tags and syntactic dependencies. Can be used out-of-the-box
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and fine-tuned on more specific data.
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2. **Starter models:** Transfer learning starter packs with pretrained weights
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you can initialize your 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 models 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 models with spaCy, see the
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[usage guide on models](/usage/models).
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</Infobox>
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## Model naming conventions {#conventions}
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In general, spaCy expects all model packages to follow the naming convention of
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`[lang`\_[name]]. For spaCy's models, we also chose to divide the name into
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three components:
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1. **Type:** Model capabilities (e.g. `core` for general-purpose model 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 model is trained on, e.g. `web` or `news`.
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3. **Size:** Model 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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model trained on written web text (blogs, news, comments), that includes
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vocabulary, vectors, syntax and entities.
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### Model versioning {#model-versioning}
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Additionally, the model versioning reflects both the compatibility with spaCy,
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as well as the major and minor model version. A model version `a.b.c` translates
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to:
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- `a`: **spaCy major version**. For example, `2` for spaCy v2.x.
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- `b`: **Model major version**. Models with a different major version can't be
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loaded by the same code. For example, changing the width of the model, adding
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hidden layers or changing the activation changes the model major version.
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- `c`: **Model minor version**. Same model structure, but different parameter
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values, e.g. from being trained on different data, for different numbers of
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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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in the models repository. This is also the source of spaCy's internal
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compatibility check, performed when you run the [`download`](/api/cli#download)
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command.
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