spaCy can be installed for a CUDA-compatible GPU by specifying spacy[cuda], spacy[cuda102], spacy[cuda112], spacy[cuda113], etc. If you know your CUDA version, using the more explicit …

Installation from Python . Since the spacy download command installs the pipeline as a Python package, we always recommend running it from the command line, just like you install other …

spaCy is a free open-source library for Natural Language Processing in Python. It features NER, POS tagging, dependency parsing, word vectors and more.

spaCy’s CLI provides a range of helpful commands for downloading and training pipelines, converting data and debugging your config, data and installation. For a list of available …

spaCy is a free open-source library for Natural Language Processing in Python. It features NER, POS tagging, dependency parsing, word vectors and more.

spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. If you’re working with a lot of text, you’ll eventually want to know more about it. For example, …

The Universe database is open-source and collected in a simple JSON file. For more details on the formats and available fields, see the documentation. Looking for inspiration your own …

The spaCy v3 trained pipelines are designed to be efficient and configurable. For example, multiple components can share a common “token-to-vector” model and it’s easy to swap out or …

The default data used is provided by the spacy-lookups-data extension package. For a trainable lemmatizer, see EditTreeLemmatizer. New in v3.0. As of v3.0, the Lemmatizer is a standalone …

The recommended way to train your spaCy pipelines is via the spacy train command on the command line. It only needs a single config.cfg configuration file that includes all settings and …