//- 💫 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.

+aside("Important note")
    |  If you're upgrading to spaCy v1.7.x or v2.x, you need to
    |  #[strong download the new models]. 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, you may suffer train/test
    |  skew, which might decrease your accuracy.

+quickstart(QUICKSTART_MODELS, "Quickstart", "Install a default model, get the code to load it from within spaCy and an example to test it. For more options, see the section on available models below.")
    - var examples = {en: "This is a sentence.", de: "Dies ist ein Satz.", fr: "C'est une phrase."}
    for models, lang in MODELS
        - var package = (models.length == 1) ? models[0] : models.find(function(m) { return m.def })
        +qs({lang: lang}) python -m spacy download #{lang}
        +qs({lang: lang}, "divider")
        +qs({lang: lang, load: "module"}, "python") import #{package.id}
        +qs({lang: lang, load: "module"}, "python") nlp = #{package.id}.load()
        +qs({lang: lang, load: "spacy"}, "python") nlp = spacy.load('#{lang}')
        +qs({lang: lang, config: "example"}, "python") doc = nlp(u"#{examples[lang]}")
        +qs({lang: lang, config: "example"}, "python") print([(w.text, w.pos_) for w in doc])

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

- var models = Object.keys(MODELS).map(function(lang) { return "python -m spacy download " + lang })
+code(false, "bash").
    # out-of-the-box: download best-matching default model
    #{Object.keys(MODELS).map(function(l) {return "python -m spacy download " + l}).join('\n')}

    # 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 a custom
    |  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 use #[code spacy.load()] to load it via its
    |  package name, create a #[+a("#usage-link") shortcut link] to assign it a
    |  custom name, or #[+a("usage-import") import it] explicitly as a module.
    |  If you need to download models as part of an automated process, we
    |  recommend using pip with a direct link, instead of relying on spaCy's
    |  #[+api("cli#download") #[code download]] command.

+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
    |  To load a model, use #[+api("spacy#load") #[code spacy.load()]] with the
    |  model's shortcut link, package name or a path to the data directory:

+code.
    import spacy
    nlp = spacy.load('en')              # load model with shortcut link "en"
    nlp = spacy.load('en_core_web_sm')  # load model package "en_core_web_sm"
    nlp = spacy.load('/path/to/model')  # load model from a directory

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

+infobox("Tip: Preview model info")
    |  You can use the #[+api("cli#info") #[code info]] command or
    |  #[+api("spacy#info") #[code spacy.info()]] method to print a model's meta data
    |  before loading it. Each #[code Language] object with a loaded model also
    |  exposes the model's meta data as the attribute #[code meta]. For example,
    |  #[code nlp.meta['version']] will return the model's version.

+h(3, "usage-link") Using custom shortcut links

p
    |  While previous versions of spaCy required you to maintain a data directory
    |  containing the models for each installation, you can now choose
    |  #[strong how and where you want to keep your data]. For example, you could
    |  download all models manually and put them into a local directory.
    |  Whenever your spaCy projects need a models, you create a shortcut link to
    |  tell spaCy to load it from there. This means you'll never end up with
    |  duplicate data.

p
    |  The #[+api("cli#link") #[code link]] command will create a symlink
    |  in the #[code spacy/data] directory.

+aside("Why does spaCy use symlinks?")
    |  Symlinks were originally introduced to maintain backwards compatibility,
    |  as older versions expected model data to live within #[code spacy/data].
    |  However, we decided to keep using them in v2.0 instead of opting for
    |  a config file. There'll always be a need for assigning and saving custom
    |  model names or IDs. And your system already comes with a native solution
    |  to mapping unicode aliases to file paths: symbolic links.

+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

+infobox("Important note")
    |  In order to create a symlink, your user needs the #[strong required permissions].
    |  If you've installed spaCy to a system directory and don't have admin
    |  privileges, the #[code spacy link] command may fail. The easiest solution
    |  is to re-run the command as admin, or use a #[code virtualenv]. For more
    |  info on this, see the
    |  #[+a("/docs/usage/troubleshooting#symlink-privilege") troubleshooting guide].

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

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

+code.
    import en_core_web_md

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

p
    |  How you choose to load your models ultimately depends on personal
    |  preference. However, #[strong for larger code bases], we usually recommend
    |  native imports, as this will make it easier to integrate models with your
    |  existing build process, continuous integration workflow and testing
    |  framework. It'll also prevent you from ever trying to load a model that
    |  is not installed, as your code will raise an #[code ImportError]
    |  immediately, instead of failing somewhere down the line when calling
    |  #[code spacy.load()].

+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 #[+api("language#to_disk") #[code Language.to_disk()]]
    |  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].