Get the latest tech news
SpaCy: Industrial-Strength Natural Language Processing (NLP) in Python
💫 Industrial-strength Natural Language Processing (NLP) in Python - explosion/spaCy
Support for 70+ languages Trained pipelines for different languages and tasks Multi-task learning with pretrained transformers like BERT Support for pretrained word vectors and embeddings State-of-the-art speed Production-ready training system Linguistically-motivated tokenization Components for named entity recognition, part-of-speech-tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking and more Easily extensible with custom components and attributes Support for custom models in PyTorch, TensorFlow and other frameworks Built in visualizers for syntax and NER Easy model packaging, deployment and workflow management Robust, rigorously evaluated accuracy If you're running spaCy v2.0 or higher, you can use the validate command to check if your installed models are compatible and if not, print details on how to update them: You'll need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, virtualenv and git installed.
Or read this on Hacker News
