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Multimodal search
taaft.com/multimodal-search
8,968 subscribers
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Number of models
5
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Models 5
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By Jina AIjina-embeddings-v5-omni is Jina AI’s multimodal embedding model suite for text, image, audio, video, and PDFs. It extends Jina’s v5 text embedding models into one shared semantic space while preserving identical text embeddings, so existing text indexes do not need rebuilding.NewMultimodalReleased 1mo ago
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By CohereMultimodal embedding model aimed at enterprise search and retrieval over multimodal data.TextReleased 4mo ago
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TextReleased 6mo ago
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By Voyage AIMultimodal embedding model that vectorizes interleaved text and images through a unified transformer encoder. Supports screenshots of PDFs, slides, tables, and figures without complex document parsing. Unlike CLIP-based models, eliminates the modality gap, enabling accurate mixed-modality retrieval across text and visual content.MultimodalReleased 1y ago
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By Caldera LabsCommand R+ is a higher-capability variant of Command R with stronger reasoning and coding while keeping the same retrieval-centric interface.TextReleased 2y ago
Repositories 5
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Discussion(1)
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Multimodal search
B34r
🙏 75 karma
2y ago
@Mixpeek
i've been trying for almost an hour to check how this works. The See Demo page takes me to a "Ask me about Tesla" page? i just want to test your product, it shouldn't be this hard -_-
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