ML watermarking

ML Watermarking offers watermarking methods to help proving ownership on the machine learning models you train.

Watermarking a machine learning model involves the incorporation of a distinct behavior, typically a modification in the model's predictions, within a specific dataset referred to as a trigger set, that this library can help you generate for classification - and in future version detection - tasks. Method and guidelines for evaluating watermarking robustness are planned to be added in future releases.

ML Watermarking is an initiative under Confiance.ai, an organization dedicated to fostering transparency, fairness, and trust in the field of artificial intelligence.