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

Algorithms for explaining machine learning models

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Interpretability and explainability of data and machine learning models

moDel Agnostic Language for Exploration and eXplanation

Generate Diverse Counterfactual Explanations for any machine learning model.

XAI - An eXplainability toolbox for machine learning

👋 Xplique is a Neural Networks Explainability Toolbox

A Discord LLM chat bot that supports any OpenAI compatible API (OpenAI, xAI, Mistral, Groq, OpenRouter, ollama, LM Studio and more)

A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI )

Neural network visualization toolkit for tf.keras

Repository for the Explainable Deep One-Class Classification paper

Layer-wise Relevance Propagation (LRP) for LSTMs.

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes

Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.

Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications

A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).

TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!