Universe

Prodigy

Radically efficient machine teaching, powered by active learning

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...

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Author info

Explosion AI

Categories standalone training

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 label on the issue tracker.

Read the docsJSON source