Prodigy
Prodigy is an annotation tool so efficient that data scientists can do the annotation themselves, enabling a new level of rapid iteration. Whether you’re working on entity recognition, intent detection or image classification, Prodigy can help you train and evaluate your models faster. Stream in your own examples or real-world data from live APIs, update your model in real-time and chain models together to build more complex systems.
Example
prodigy dataset ner_product "Improve PRODUCT on Reddit data" ✨ Created dataset 'ner_product'. prodigy ner.teach ner_product en_core_web_sm ~/data.jsonl --label PRODUCT ✨ Starting the web server on port 8080...
Categories standalone training
Found a mistake or something isn't working?
If you've come across a universe project that isn't working or is incompatible with the reported spaCy version, let us know by opening a discussion thread.
Submit your project
If you have a project that you want the spaCy community to make use of, you can suggest it by submitting a pull request to the spaCy website repository. 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 spaCy plugin or extension? Check out the project idea section in Discussions.