Abstract
Nomic-embed-vision and nomic-embed-text form a unified latent space for high-performance vision, language, and multimodal tasks.
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This technical report describes the training of nomic-embed-vision, a highly performant, open-code, open-weights image embedding model that shares the same latent space as nomic-embed-text. Together, nomic-embed-vision and nomic-embed-text form the first unified latent space to achieve high performance across vision, language, and multimodal tasks.
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