spaCy

spaCy

spaCy is a production-ready, industrial-strength NLP library for Python and Cython. It provides pre-trained pipelines for 65+ languages and is designed from the ground up for real applications — prioritizing speed, accuracy, and a clean developer API.

Key Features

• Pre-trained pipelines: Named entity recognition (NER), part-of-speech tagging, dependency parsing, text classification, and sentence segmentation — out of the box for 65+ languages
• Transformer models: Seamlessly integrate BERT, RoBERTa, or any HuggingFace model as a spaCy component
• Custom components: Extend pipelines with your own processing steps using @Language.component
• Rule-based matching: Matcher and PhraseMatcher for regex-like matching over linguistic annotations
• spaCy Projects: Reproducible NLP workflows with config files, versioning, and remote storage
• Speed: Written in Cython — 5–10x faster than NLTK on most tasks

Quick Start

pip install spacy
python -m spacy download en_core_web_sm

import spacy

nlp = spacy.load("en_core_web_sm")
doc = nlp("Apple is building a new AI campus in London.")

for ent in doc.ents:
    print(ent.text, ent.label_)
# Apple ORG  |  London GPE

Add to ai-supply

npx ai-supply add spacy-nlp-library

Curated mirror of the open-source spaCy (MIT). Get it from the source.