//- 💫 DOCS > USAGE > MODELS

include ../../_includes/_mixins

p
    |  As of v1.7.0, models for spaCy can be installed as #[strong Python packages].
    |  This means that they're a component of your application, just like any
    |  other module. They're versioned and can be defined as a dependency in your
    |  #[code requirements.txt]. Models can be installed from a download URL or
    |  a local directory, manually or via #[+a("https://pypi.python.org/pypi/pip") pip].
    |  Their data can be located anywhere on your file system. To make a model
    |  available to spaCy, all you need to do is create a "shortcut link", an
    |  internal alias that tells spaCy where to find the data files for a specific
    |  model name.

+aside-code("Quickstart").
    # Install spaCy and download English model
    pip install spacy
    python -m spacy download en

    # Usage in Python
    import spacy
    nlp = spacy.load('en')
    doc = nlp(u'This is a sentence.')

+infobox("Important note")
    |  Due to improvements in the English lemmatizer in v1.7.0, you need to
    |  #[strong download the new English models]. The German model is still
    |  compatible. If you've trained statistical models that use spaCy's
    |  annotations, you should #[strong retrain your models after updating spaCy].
    |  If you don't retrain your models, you may suffer train/test skew, which
    |  might decrease your accuracy.

+h(2, "available") Available models

include _models-list

+h(2, "download") Downloading models

+aside("Downloading models in spaCy < v1.7")
    |  In older versions of spaCy, you can still use the old download commands.
    |  This will download and install the models into the #[code spacy/data]
    |  directory.

    +code.o-no-block.
        python -m spacy.en.download all
        python -m spacy.de.download all
        python -m spacy.en.download glove

    |  The old models are also #[+a(gh("spacy") + "/tree/v1.6.0") attached to the v1.6.0 release].
    |  To download and install them manually, unpack the archive, drop the
    |  contained directory into #[code spacy/data] and load the model via
    |  #[code spacy.load('en')] or #[code spacy.load('de')].

p
    |  The easiest way to download a model is via spaCy's #[code download]
    |  command. It takes care of finding the best-matching model compatible with
    |  your spaCy installation.

+code(false, "bash").
    # out-of-the-box: download best-matching default model
    python -m spacy download en
    python -m spacy download de
    python -m spacy download fr

    # download best-matching version of specific model for your spaCy installation
    python -m spacy download en_core_web_md

    # download exact model version (doesn't create shortcut link)
    python -m spacy download en_core_web_md-1.2.0 --direct

p
    |  The download command will #[+a("#download-pip") install the model] via
    |  pip, place the package in your #[code site-packages] directory and create
    |  a #[+a("#usage") shortcut link] that lets you load the model by name. The
    |  shortcut link will be the same as the model name used in
    |  #[code spacy.download].

+code(false, "bash").
    pip install spacy
    python -m spacy download en

+code.
    import spacy
    nlp = spacy.load('en')
    doc = nlp(u'This is a sentence.')

+h(3, "download-pip") Installation via pip

p
    | To download a model directly using #[+a("https://pypi.python.org/pypi/pip") pip],
    |  simply point #[code pip install] to the URL or local path of the archive
    |  file. To find the direct link to a model, head over to the
    |  #[+a(gh("spacy-models") + "/releases") model releases], right click on the archive
    |  link and copy it to your clipboard.

+code(false, "bash").
    # with external URL
    pip install #{gh("spacy-models")}/releases/download/en_core_web_md-1.2.0/en_core_web_md-1.2.0.tar.gz

    # with local file
    pip install /Users/you/en_core_web_md-1.2.0.tar.gz

p
    |  By default, this will install the model into your #[code site-packages]
    |  directory. You can then create a #[+a("#usage") shortcut link] for your
    |  model to load it via #[code spacy.load()], or #[+a("usage-import") import it]
    |  as a Python module.

+h(3, "download-manual") Manual download and installation

p
    |  In some cases, you might prefer downloading the data manually, for
    |  example to place it into a custom directory. You can download the model
    |  via your browser from the #[+a(gh("spacy-models")) latest releases], or configure
    |  your own download script using the URL of the archive file. The archive
    |  consists of a model directory that contains another directory with the
    |  model data.

+code("Directory structure", "yaml").
    └── en_core_web_md-1.2.0.tar.gz       # downloaded archive
        ├── meta.json                     # model meta data
        ├── setup.py                      # setup file for pip installation
        └── en_core_web_md                # model directory
            ├── __init__.py               # init for pip installation
            ├── meta.json                 # model meta data
            └── en_core_web_md-1.2.0      # model data

p
    |  You can place the model data directory anywhere on your local file system.
    |  To use it with spaCy, simply assign it a name by creating a
    |  #[+a("#usage") shortcut link] for the data directory.

+h(2, "usage") Using models with spaCy

p
    |  While previous versions of spaCy required you to maintain a data directory
    |  containing the models for each installation, you can now choose how and
    |  where you want to keep your data files. To load the models conveniently
    |  from within spaCy, you can use the #[code spacy.link] command to create a
    |  symlink. This lets you set up custom shortcut links for models so you can
    |  load them by name.

+code(false, "bash").
    python -m spacy link [package name or path] [shortcut] [--force]

p
    |  The first argument is the package name (if the model was installed via
    |  pip), or a local path to the the data directory. The second argument is
    |  the internal name you want to use for the model. Setting the #[code --force]
    |  flag will overwrite any existing links.

+code("Examples", "bash").
    # set up shortcut link to load installed package as "en_default"
    python -m spacy link en_core_web_md en_default

    # set up shortcut link to load local model as "my_amazing_model"
    python -m spacy link /Users/you/model my_amazing_model

+h(3, "usage-loading") Loading models

p
    |  To load a model, use #[code spacy.load()] with the model's shortcut link.

+code.
    import spacy
    nlp = spacy.load('en_default')
    doc = nlp(u'This is a sentence.')

p
    |  You can also use the #[info] command or #[code info()] method to print a model's meta data
    |  before loading it. Each #[code Language] object returned by #[code spacy.load()]
    |  also exposes the model's meta data as the attribute #[code meta].

+code(false, "bash").
    python -m spacy info en
    # model meta data

+code.
    import spacy
    spacy.info('en_default')
    # model meta data

    nlp = spacy.load('en_default')
    print(nlp.meta['version'])
    # 1.2.0

+h(3, "usage-import") Importing models as modules

p
    |  If you've installed a model via pip, you can also #[code import] it
    |  directly and then call its #[code load()] method with no arguments:

+code.
    import spacy
    import en_core_web_md

    nlp = en_core_web_md.load()
    doc = nlp(u'This is a sentence.')

+h(2, "own-models") Using your own models

p
    |  If you've trained your own model, for example for
    |  #[+a("/docs/usage/adding-languages") additional languages] or
    |  #[+a("/docs/usage/train-ner") custom named entities], you can save its
    |  state using the #[code Language.save_to_directory()] method. To make the
    |  model more convenient to deploy, we recommend wrapping it as a Python
    |  package.

+infobox("Saving and loading models")
    |  For more information and a detailed guide on how to package your model,
    |  see the documentation on
    |  #[+a("/docs/usage/saving-loading") saving and loading models].