A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
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Updated
Jun 2, 2024
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
An in-depth performance profiling library for machine learning models
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 AI, Trustworthy AI, and Human-Centered AI.
🐢 Open-Source Evaluation & Testing for LLMs and ML models
The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.
Deliver safe & effective language models
A Python package to assess and improve fairness of machine learning models.
We make Generative AI accessible to Federal agencies and businesses. Easy-to-use ezGPT™ platform eliminates the need for in-house expertise and delivers pre-built solutions for rapid innovation. With security and privacy at its core, we unlock the potential of AI. Our innovative chatbot guides users, ensuring a smooth and successful experience.
We make Generative AI accessible to Federal agencies and businesses. Easy-to-use ezGPT™ platform eliminates the need for in-house expertise and delivers pre-built solutions for rapid innovation. With security and privacy at its core, we unlock the potential of AI. Our innovative chatbot guides users, ensuring a smooth and successful experience.
Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
Artificial Intelligence & Machine Learning (AIML) group
moDel Agnostic Language for Exploration and eXplanation
Concise summaries of key papers in responsible AI.
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.
🤖🛡️🔍🔒🔑 Tiny package designed to support red teams and penetration testers in exploiting large language model AI solutions.
Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice
Trustworthy AI/ML course by Professor Birhanu Eshete, University of Michigan, Dearborn.
Responsible and Safe AI practices. Studying and recommending solutions for Identifying memorization by Large Language Models
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