Using and customizing the models
spaCy comes with free pre-trained models for lots of languages, but there are many more that the
default models don't cover. Even if we do provide a model
that does what you need, it's almost always useful to update
the models with some annotated examples for your specific problem. Our annotation tool Prodigy can help you efficiently label data to train, improve and
evaluate your models.
Download modelsTry Prodigy
displaCy Dependency Visualizer
spaCy also comes with a built-in dependency visualizer that lets you check your model's
predictions in your browser. You can pass in one or more Doc
objects and start a web server, export HTML files or view the visualization directly from a Jupyter
Notebook.
import spacy
nlp = spacy.load("en_core_web_sm")
doc = nlp("displaCy uses JavaScript, SVG and CSS.")
spacy.displacy.serve(doc, style="dep")
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