Trustworthy Machine Learning Python Packages

infairness

PyTorch package to train and audit ML models for Individual Fairness

torch-uncertainty

Open-source framework for uncertainty and deep learning models in PyTorch 🌱

trustllm

[ICML 2024] TrustLLM: LLM trustworthiness evaluation across truthfulness, safety, fairness, robustness, privacy and ethics. Python/CLI toolkit for local models, compatible APIs and AI agent orchestration.

advsecurenet

Machine Learning Security Library

strep

Initiating a paradigm shift in reporting and helping with making ML advances more considerate of sustainability and trustworthiness.

approx-cp

Implementation for the paper "Approximating full conformal prediction at scale via influence functions"

famework

Framework for Adversarial Malware Evaluation.

pysyrenn

SyReNN: Symbolic Representations for Neural Networks

robust-deep-learning

A project to train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.

contrxt

a tool for comparing the predictions of any text classifiers

lime-stratified

[AAAI-24 Paper] Using Stratified Sampling to improve LIME image explanations

prdnn

Code from PLDI '21 paper "Provable Repair of Deep Neural Networks."