There are 10 repositories under responsible-ai topic.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
🐢 Open-Source Evaluation & Testing for AI & LLM systems
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
moDel Agnostic Language for Exploration and eXplanation
Deliver safe & effective language models
A toolkit that streamlines and automates the generation of model cards
💡 Adversarial attacks on explanations and how to defend them
Carefully curated list of awesome data science resources.
A detailed summary of "Designing Machine Learning Systems" by Chip Huyen. This book gives you and end-to-end view of all the steps required to build AND OPERATE ML products in production. It is a must-read for ML practitioners and Software Engineers Transitioning into ML.
[NeurIPS 2023] Sentry-Image: Detect Any AI-generated Images
Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
Reading list for adversarial perspective and robustness in deep reinforcement learning.
This is an open-source tool to assess and improve the trustworthiness of AI systems.
Référentiel d'évaluation data science responsable et de confiance
[ICCV 2023 Oral, Best Paper Finalist] ITI-GEN: Inclusive Text-to-Image Generation
A collection of news articles, books, and papers on Responsible AI cases. The purpose is to study these cases and learn from them to avoid repeating the failures of the past.
PyTorch package to train and audit ML models for Individual Fairness
Python library for implementing Responsible AI mitigations.
A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible, Trustworthy, and Human-Centered AI.
Credo AI Lens is a comprehensive assessment framework for AI systems. Lens standardizes model and data assessment, and acts as a central gateway to assessments created in the open source community.
Oracle Guardian AI Open Source Project is a library consisting of tools to assess fairness/bias and privacy of machine learning models and data sets.
Official code of "StyleT2I: Toward Compositional and High-Fidelity Text-to-Image Synthesis" (CVPR 2022)
Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice
An open-content programming cookbook. A responsible use of AI proof of concept. Collaborative, polyglot and multilingual.
Official code of "Discover and Mitigate Unknown Biases with Debiasing Alternate Networks" (ECCV 2022)
This framework aims to assists in the documentation of datasets to promote transparency and help dataset creators and consumers make informed decisions about whether specific datasets meet their needs and what limitations they need to consider
Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
AART: AI-Assisted Red-Teaming with Diverse Data Generation for New LLM-powered Applications
Explore/examine/explain/expose your model with the explabox!