spaCy v3.0 is a huge release! It features new transformer-based pipelines that get spaCy’s accuracy right up to the current state-of-the-art, and a new workflow system to help you take projects from prototype to production. It’s much easier to configure and train your pipeline, and there are lots of new and improved integrations with the rest of the NLP ecosystem.

Our main aim with the release is to make it easier to bring your own models into spaCy, especially state-of-the-art models like transformers. You can write models powering spaCy components in frameworks like PyTorch or TensorFlow, using our awesome new configuration system to describe all of your settings. And since modern NLP workflows often consist of multiple steps, there’s a new workflow system to help you keep your work organized.

Enjoy!

→  Authors: Matthew Honnibal, Ines Montani, Sofie Van Landeghem, Adriane Boyd

→  Blog post: Full post

→  Repo: Github