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Awesome GitHub RepositoriesModel Auditing Tools
Frameworks and utilities for evaluating machine learning models for bias, fairness, and performance disparities.
Distinguishing note: Focuses on ethical and performance auditing of models rather than general model training or deployment.
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Awesome Model Auditing Tools GitHub Repositories
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- openai/CLIP
openai/CLIP
32,614View on GitHubCLIP is a neural network architecture designed to map visual and textual data into a shared latent vector space. By utilizing transformer-based feature extraction and multi-modal tokenization, the system aligns images and natural language strings, enabling cross-modal similarity analysis and semantic classification. The project functions as a zero-shot classification engine, identifying image content by calculating the cosine similarity between visual features and arbitrary text labels without requiring task-specific retraining. Beyond inference, it serves as a research toolkit for evaluating
Analyzing machine learning models to detect performance disparities and potential risks related to unfair treatment of sensitive demographic groups.
Jupyter Notebookdeep-learningmachine-learning
