interpretml/interpret

A game theoretic approach to explain the output of any machine learning model.

Lime: Explaining the predictions of any machine learning classifier

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

Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization

⚡ TabPFN: Foundation Model for Tabular Data ⚡

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Give your agents the power of the Hugging Face ecosystem

ModelScope: bring the notion of Model-as-a-Service to life.