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184 lines
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184 lines
8.0 KiB
Plaintext
//- 💫 DOCS > USAGE > MODELS > INSTALLATION
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+aside("Downloading models in spaCy < v1.7")
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| In older versions of spaCy, you can still use the old download commands.
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| This will download and install the models into the #[code spacy/data]
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| directory.
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+code.o-no-block.
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python -m spacy.en.download all
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python -m spacy.de.download all
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python -m spacy.en.download glove
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| The old models are also #[+a(gh("spacy") + "/tree/v1.6.0") attached to the v1.6.0 release].
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| To download and install them manually, unpack the archive, drop the
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| contained directory into #[code spacy/data].
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include _install-basics
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+h(3, "download-pip") Installation via pip
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p
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| To download a model directly using #[+a("https://pypi.python.org/pypi/pip") pip],
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| simply point #[code pip install] to the URL or local path of the archive
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| file. To find the direct link to a model, head over to the
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| #[+a(gh("spacy-models") + "/releases") model releases], right click on the archive
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| link and copy it to your clipboard.
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+code(false, "bash").
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# with external URL
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pip install #{gh("spacy-models")}/releases/download/en_core_web_md-1.2.0/en_core_web_md-1.2.0.tar.gz
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# with local file
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pip install /Users/you/en_core_web_md-1.2.0.tar.gz
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p
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| By default, this will install the model into your #[code site-packages]
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| directory. You can then use #[code spacy.load()] to load it via its
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| package name, create a #[+a("#usage-link") shortcut link] to assign it a
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| custom name, or #[+a("#usage-import") import it] explicitly as a module.
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| If you need to download models as part of an automated process, we
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| recommend using pip with a direct link, instead of relying on spaCy's
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| #[+api("cli#download") #[code download]] command.
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+infobox
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| You can also add the direct download link to your application's
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| #[code requirements.txt]. For more details,
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| see the section on
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| #[+a("/models/#production") working with models in production].
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+h(3, "download-manual") Manual download and installation
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p
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| In some cases, you might prefer downloading the data manually, for
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| example to place it into a custom directory. You can download the model
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| via your browser from the #[+a(gh("spacy-models")) latest releases], or configure
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| your own download script using the URL of the archive file. The archive
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| consists of a model directory that contains another directory with the
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| model data.
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+code("Directory structure", "yaml").
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└── en_core_web_md-1.2.0.tar.gz # downloaded archive
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├── meta.json # model meta data
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├── setup.py # setup file for pip installation
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└── en_core_web_md # 📦 model package
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├── __init__.py # init for pip installation
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├── meta.json # model meta data
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└── en_core_web_md-1.2.0 # model data
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p
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| You can place the #[strong model package directory] anywhere on your
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| local file system. To use it with spaCy, simply assign it a name by
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| creating a #[+a("#usage") shortcut link] for the data directory.
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+h(3, "usage") Using models with spaCy
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p
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| To load a model, use #[+api("spacy#load") #[code spacy.load()]] with the
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| model's shortcut link, package name or a path to the data directory:
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+code.
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import spacy
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nlp = spacy.load('en') # load model with shortcut link "en"
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nlp = spacy.load('en_core_web_sm') # load model package "en_core_web_sm"
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nlp = spacy.load('/path/to/en_core_web_sm') # load package from a directory
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doc = nlp(u'This is a sentence.')
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+infobox("Tip: Preview model info")
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| You can use the #[+api("cli#info") #[code info]] command or
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| #[+api("spacy#info") #[code spacy.info()]] method to print a model's meta data
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| before loading it. Each #[code Language] object with a loaded model also
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| exposes the model's meta data as the attribute #[code meta]. For example,
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| #[code nlp.meta['version']] will return the model's version.
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+h(3, "usage-link") Using custom shortcut links
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p
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| While previous versions of spaCy required you to maintain a data directory
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| containing the models for each installation, you can now choose
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| #[strong how and where you want to keep your data]. For example, you could
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| download all models manually and put them into a local directory.
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| Whenever your spaCy projects need a models, you create a shortcut link to
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| tell spaCy to load it from there. This means you'll never end up with
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| duplicate data.
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p
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| The #[+api("cli#link") #[code link]] command will create a symlink
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| in the #[code spacy/data] directory.
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+aside("Why does spaCy use symlinks?")
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| Symlinks were originally introduced to maintain backwards compatibility,
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| as older versions expected model data to live within #[code spacy/data].
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| However, we decided to keep using them in v2.0 instead of opting for
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| a config file. There'll always be a need for assigning and saving custom
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| model names or IDs. And your system already comes with a native solution
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| to mapping unicode aliases to file paths: symbolic links.
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+code(false, "bash", "$").
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spacy link [package name or path] [shortcut] [--force]
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p
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| The first argument is the #[strong package name] (if the model was
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| installed via pip), or a local path to the the #[strong model package].
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| The second argument is the internal name you want to use for the model.
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| Setting the #[code --force] flag will overwrite any existing links.
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+code("Examples", "bash").
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# set up shortcut link to load installed package as "en_default"
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spacy link en_core_web_md en_default
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# set up shortcut link to load local model as "my_amazing_model"
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spacy link /Users/you/model my_amazing_model
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+infobox("Important note")
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| In order to create a symlink, your user needs the #[strong required permissions].
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| If you've installed spaCy to a system directory and don't have admin
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| privileges, the #[code spacy link] command may fail. The easiest solution
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| is to re-run the command as admin, or use a #[code virtualenv]. For more
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| info on this, see the
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| #[+a("/usage/#symlink-privilege") troubleshooting guide].
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+h(3, "usage-import") Importing models as modules
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p
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| If you've installed a model via spaCy's downloader, or directly via pip,
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| you can also #[code import] it and then call its #[code load()] method
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| with no arguments:
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+code.
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import en_core_web_md
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nlp = en_core_web_md.load()
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doc = nlp(u'This is a sentence.')
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p
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| How you choose to load your models ultimately depends on personal
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| preference. However, #[strong for larger code bases], we usually recommend
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| native imports, as this will make it easier to integrate models with your
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| existing build process, continuous integration workflow and testing
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| framework. It'll also prevent you from ever trying to load a model that
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| is not installed, as your code will raise an #[code ImportError]
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| immediately, instead of failing somewhere down the line when calling
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| #[code spacy.load()].
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+infobox
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| For more details, see the section on
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| #[+a("/models/#production") working with models in production].
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+h(3, "own-models") Using your own models
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p
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| If you've trained your own model, for example for
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| #[+a("/usage/adding-languages") additional languages] or
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| #[+a("/usage/training#ner") custom named entities], you can save its
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| state using the #[+api("language#to_disk") #[code Language.to_disk()]]
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| method. To make the model more convenient to deploy, we recommend
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| wrapping it as a Python package.
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+infobox("Saving and loading models")
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| For more information and a detailed guide on how to package your model,
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| see the documentation on
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| #[+a("/usage/training#saving-loading") saving and loading models].
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