mirror of https://github.com/explosion/spaCy.git
158 lines
5.1 KiB
Plaintext
158 lines
5.1 KiB
Plaintext
//- 💫 DOCS > API > TOP-LEVEL > SPACY
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+h(3, "spacy.load") spacy.load
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+tag function
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+tag-model
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p
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| Load a model via its #[+a("/usage/models#usage") shortcut link],
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| the name of an installed
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| #[+a("/usage/training#models-generating") model package], a unicode
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| path or a #[code Path]-like object. spaCy will try resolving the load
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| argument in this order. If a model is loaded from a shortcut link or
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| package name, spaCy will assume it's a Python package and import it and
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| call the model's own #[code load()] method. If a model is loaded from a
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| path, spaCy will assume it's a data directory, read the language and
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| pipeline settings off the meta.json and initialise the #[code Language]
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| class. The data will be loaded in via
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| #[+api("language#from_disk") #[code Language.from_disk()]].
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+aside-code("Example").
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nlp = spacy.load('en') # shortcut link
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nlp = spacy.load('en_core_web_sm') # package
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nlp = spacy.load('/path/to/en') # unicode path
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nlp = spacy.load(Path('/path/to/en')) # pathlib Path
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nlp = spacy.load('en', disable=['parser', 'tagger'])
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code name]
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+cell unicode or #[code Path]
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+cell Model to load, i.e. shortcut link, package name or path.
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+row
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+cell #[code disable]
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+cell list
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+cell
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| Names of pipeline components to
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| #[+a("/usage/processing-pipelines#disabling") disable].
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+row("foot")
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+cell returns
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+cell #[code Language]
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+cell A #[code Language] object with the loaded model.
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p
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| Essentially, #[code spacy.load()] is a convenience wrapper that reads
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| the language ID and pipeline components from a model's #[code meta.json],
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| initialises the #[code Language] class, loads in the model data and
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| returns it.
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+code("Abstract example").
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cls = util.get_lang_class(lang) # get language for ID, e.g. 'en'
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nlp = cls() # initialise the language
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for name in pipeline:
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component = nlp.create_pipe(name) # create each pipeline component
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nlp.add_pipe(component) # add component to pipeline
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nlp.from_disk(model_data_path) # load in model data
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+infobox("Deprecation note", "⚠️")
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.o-block
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| As of spaCy 2.0, the #[code path] keyword argument is deprecated. spaCy
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| will also raise an error if no model could be loaded and never just
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| return an empty #[code Language] object. If you need a blank language,
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| you can use the new function #[+api("spacy#blank") #[code spacy.blank()]]
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| or import the class explicitly, e.g.
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| #[code from spacy.lang.en import English].
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+code-new nlp = spacy.load('/model')
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+code-old nlp = spacy.load('en', path='/model')
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+h(3, "spacy.blank") spacy.blank
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+tag function
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+tag-new(2)
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p
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| Create a blank model of a given language class. This function is the
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| twin of #[code spacy.load()].
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+aside-code("Example").
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nlp_en = spacy.blank('en')
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nlp_de = spacy.blank('de')
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code name]
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+cell unicode
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+cell ISO code of the language class to load.
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+row
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+cell #[code disable]
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+cell list
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+cell
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| Names of pipeline components to
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| #[+a("/usage/processing-pipelines#disabling") disable].
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+row("foot")
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+cell returns
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+cell #[code Language]
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+cell An empty #[code Language] object of the appropriate subclass.
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+h(4, "spacy.info") spacy.info
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+tag function
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p
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| The same as the #[+api("cli#info") #[code info] command]. Pretty-print
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| information about your installation, models and local setup from within
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| spaCy. To get the model meta data as a dictionary instead, you can
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| use the #[code meta] attribute on your #[code nlp] object with a
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| loaded model, e.g. #[code nlp['meta']].
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+aside-code("Example").
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spacy.info()
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spacy.info('en')
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spacy.info('de', markdown=True)
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code model]
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+cell unicode
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+cell A model, i.e. shortcut link, package name or path (optional).
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+row
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+cell #[code markdown]
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+cell bool
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+cell Print information as Markdown.
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+h(3, "spacy.explain") spacy.explain
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+tag function
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p
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| Get a description for a given POS tag, dependency label or entity type.
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| For a list of available terms, see
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| #[+src(gh("spacy", "spacy/glossary.py")) #[code glossary.py]].
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+aside-code("Example").
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spacy.explain('NORP')
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# Nationalities or religious or political groups
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doc = nlp(u'Hello world')
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for word in doc:
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print(word.text, word.tag_, spacy.explain(word.tag_))
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# Hello UH interjection
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# world NN noun, singular or mass
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code term]
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+cell unicode
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+cell Term to explain.
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+row("foot")
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+cell returns
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+cell unicode
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+cell The explanation, or #[code None] if not found in the glossary.
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