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A Billion-Scale Retrieval System for Text-to-Image Training Data
Training a text-to-image model from scratch means finding, inspecting and filtering samples across billions of image–text pairs. Using a retrieval system over 1.4B samples as an example, this post covers data storage and management, distributed embedding extraction, building and querying an IVF-PQ index, and online retrieval and cluster browsing.