Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Interpretability and explainability of data and machine learning models

Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

Diffusers-Interpret 🤗🧨🕵️‍♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.

A standardized Python API with necessary preprocessing, machine learning and explainability tools to facilitate graph-analytics in computational pathology.