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Perplexity Open-Sources Embedding Models
Perplexity open-sources pplx-embed-v2-late 9B and 0.6B multi-vector embedding models, scoring 92.4% on MADQA, weights on Hugging Face.
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We’re open-sourcing pplx-embed-v2-late, multi-vector embeddings for text and images, 9B and 0.6B, in one shared embedding space. You can use these to index multimodal data with 9B, and query on device with 0.6B. This also enables you to search over PDF pages with no OCR. And scores 92.4% on MADQA, 64% on BrowseComp+. Weights available on @huggingface now.Quoting @perplexity_ai: We're releasing pplx-embed-v2-late, two late-interaction embedding models that retrieve text, images, and pages with a shared embedding space for cross-model querying.
Both models achieve frontier performance and are publicly available on Hugging Face.
https://t.co/AM7YEyQkKE https://t.co/fR8kaYmHs1
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