Here are
113 public repositories
matching this topic...
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
?? Open-Source Evaluation & Testing for LLMs and ML models
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Jun 13, 2024
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Python
A Python package to assess and improve fairness of machine learning models.
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Jun 13, 2024
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Python
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.
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Jun 13, 2024
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Python
moDel Agnostic Language for Exploration and eXplanation
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Jun 9, 2024
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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.
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May 21, 2024
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TypeScript
Deliver safe & effective language models
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Jun 13, 2024
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Python
A toolkit that streamlines and automates the generation of model cards
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Jul 26, 2023
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?? Adversarial attacks on explanations and how to defend them
Official code repo for the O'Reilly Book - Machine Learning for High-Risk Applications
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May 23, 2023
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Jupyter Notebook
Reading list for adversarial perspective and robustness in deep reinforcement learning.
[NeurIPS 2023] Sentry-Image: Detect Any AI-generated Images
Carefully curated list of awesome data science resources.
Referentiel d'evaluation data science responsable et de confiance
PyTorch package to train and audit ML models for Individual Fairness
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Sep 14, 2023
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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.
[ICCV 2023 Oral, Best Paper Finalist] ITI-GEN: Inclusive Text-to-Image Generation
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Feb 16, 2024
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Python
Python library for implementing Responsible AI mitigations.
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Dec 17, 2023
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Jupyter Notebook
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.
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.
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Jun 13, 2024
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Python
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