//- 💫 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]