spaCy/website/api/_top-level/_spacy.jade

//- 💫 DOCS > API > TOP-LEVEL > SPACY

+h(3, "spacy.load") spacy.load
    +tag function
    +tag-model

p
    |  Load a model via its #[+a("/usage/models#usage") shortcut link],
    |  the name of an installed
    |  #[+a("/usage/training#models-generating") model package], a unicode
    |  path or a #[code Path]-like object. spaCy will try resolving the load
    |  argument in this order. If a model is loaded from a shortcut link or
    |  package name, spaCy will assume it's a Python package and import it and
    |  call the model's own #[code load()] method. If a model is loaded from a
    |  path, spaCy will assume it's a data directory, read the language and
    |  pipeline settings off the meta.json and initialise the #[code Language]
    |  class. The data will be loaded in via
    |  #[+api("language#from_disk") #[code Language.from_disk()]].

+aside-code("Example").
    nlp = spacy.load('en') # shortcut link
    nlp = spacy.load('en_core_web_sm') # package
    nlp = spacy.load('/path/to/en') # unicode path
    nlp = spacy.load(Path('/path/to/en')) # pathlib Path

    nlp = spacy.load('en', disable=['parser', 'tagger'])

+table(["Name", "Type", "Description"])
    +row
        +cell #[code name]
        +cell unicode or #[code Path]
        +cell Model to load, i.e. shortcut link, package name or path.

    +row
        +cell #[code disable]
        +cell list
        +cell
            |  Names of pipeline components to
            |  #[+a("/usage/processing-pipelines#disabling") disable].

    +row("foot")
        +cell returns
        +cell #[code Language]
        +cell A #[code Language] object with the loaded model.

p
    |  Essentially, #[code spacy.load()] is a convenience wrapper that reads
    |  the language ID and pipeline components from a model's #[code meta.json],
    |  initialises the #[code Language] class, loads in the model data and
    |  returns it.

+code("Abstract example").
    cls = util.get_lang_class(lang)         #  get language for ID, e.g. 'en'
    nlp = cls()                             #  initialise the language
    for name in pipeline:
        component = nlp.create_pipe(name)   #  create each pipeline component
        nlp.add_pipe(component)             #  add component to pipeline
    nlp.from_disk(model_data_path)          #  load in model data

+infobox("Changed in v2.0", "⚠️")
    |  As of spaCy 2.0, the #[code path] keyword argument is deprecated. spaCy
    |  will also raise an error if no model could be loaded and never just
    |  return an empty #[code Language] object. If you need a blank language,
    |  you can use the new function #[+api("spacy#blank") #[code spacy.blank()]]
    |  or import the class explicitly, e.g.
    |  #[code from spacy.lang.en import English].

    +code-wrapper
        +code-new nlp = spacy.load('/model')
        +code-old nlp = spacy.load('en', path='/model')

+h(3, "spacy.blank") spacy.blank
    +tag function
    +tag-new(2)

p
    |  Create a blank model of a given language class. This function is the
    |  twin of #[code spacy.load()].

+aside-code("Example").
    nlp_en = spacy.blank('en')
    nlp_de = spacy.blank('de')

+table(["Name", "Type", "Description"])
    +row
        +cell #[code name]
        +cell unicode
        +cell
            |  #[+a("https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes") ISO code]
            |  of the language class to load.

    +row
        +cell #[code disable]
        +cell list
        +cell
            |  Names of pipeline components to
            |  #[+a("/usage/processing-pipelines#disabling") disable].

    +row("foot")
        +cell returns
        +cell #[code Language]
        +cell An empty #[code Language] object of the appropriate subclass.


+h(4, "spacy.info") spacy.info
    +tag function

p
    |  The same as the #[+api("cli#info") #[code info] command]. Pretty-print
    |  information about your installation, models and local setup from within
    |  spaCy. To get the model meta data as a dictionary instead, you can
    |  use the #[code meta] attribute on your #[code nlp] object with a
    |  loaded model, e.g. #[code nlp.meta].

+aside-code("Example").
    spacy.info()
    spacy.info('en')
    spacy.info('de', markdown=True)

+table(["Name", "Type", "Description"])
    +row
        +cell #[code model]
        +cell unicode
        +cell A model, i.e. shortcut link, package name or path (optional).

    +row
        +cell #[code markdown]
        +cell bool
        +cell Print information as Markdown.


+h(3, "spacy.explain") spacy.explain
    +tag function

p
    |  Get a description for a given POS tag, dependency label or entity type.
    |  For a list of available terms, see
    |  #[+src(gh("spacy", "spacy/glossary.py")) #[code glossary.py]].

+aside-code("Example").
    spacy.explain(u'NORP')
    # Nationalities or religious or political groups

    doc = nlp(u'Hello world')
    for word in doc:
        print(word.text, word.tag_, spacy.explain(word.tag_))
    # Hello UH interjection
    # world NN noun, singular or mass

+table(["Name", "Type", "Description"])
    +row
        +cell #[code term]
        +cell unicode
        +cell Term to explain.

    +row("foot")
        +cell returns
        +cell unicode
        +cell The explanation, or #[code None] if not found in the glossary.

+h(3, "spacy.prefer_gpu") spacy.prefer_gpu
    +tag function
    +tag-new("2.0.14")

p
    |  Allocate data and perform operations on #[+a("/usage/#gpu") GPU], if
    |  available. If data has already been allocated on CPU, it will not be
    |  moved. Ideally, this function should be called right after
    |  importing spaCy and #[em before] loading any models.

+aside-code("Example").
    import spacy
    activated = spacy.prefer_gpu()
    nlp = spacy.load('en_core_web_sm')

+table(["Name", "Type", "Description"])
    +row("foot")
        +cell returns
        +cell bool
        +cell Whether the GPU was activated.

+h(3, "spacy.require_gpu") spacy.require_gpu
    +tag function
    +tag-new("2.0.14")

p
    |  Allocate data and perform operations on #[+a("/usage/#gpu") GPU]. Will
    |  raise an error if no GPU is available. If data has already been allocated
    |  on CPU, it will not be moved. Ideally, this function should be called
    |  right after importing spaCy and #[em before] loading any models.

+aside-code("Example").
    import spacy
    spacy.require_gpu()
    nlp = spacy.load('en_core_web_sm')

+table(["Name", "Type", "Description"])
    +row("foot")
        +cell returns
        +cell bool
        +cell #[code True]