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Run LLMs Locally adds EmbeddingGemma2 multimodal embeddings

Original: New update: Run LLMs Locally Added EmbeddingGemma2 using llama.cpp. It includes multi modality, allowing to generate emb

A developer released an update to Run LLMs Locally adding EmbeddingGemma2 support via llama.cpp. The new version handles multimodal inputs, generating embedding vectors from text, images, video, and audio, which makes it possible to build local search engines over documents and photos. The project is available on GitHub, and it is drawing attention among people interested in running AI tools offline on their own hardware.

Why now: Local, privacy-friendly multimodal AI search is a trending topic among open-source AI enthusiasts.

Run LLMs LocallyEmbeddingGemma2llama.cpp

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Evidence

• New update: Run LLMs Locally Added EmbeddingGemma2 using llama.cpp. It includes multi modality, allowing to generate embedding vectors from text, images, video, and audio. So you build a search engine for documents and photos. https:// github.com/thomas-0816/talks/b… · thbley@phpc.social · 4

API: https://socialmediatrends-api.osmike.com/v1/trends/1286148