Awesome GitHub RepositoriesModel Fairness Auditing Tools

CLIP 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

The library provides model fairness assessment to test performance disparities across demographic groups and uncover potential risks related to inaccurate classification or unfair treatment.