Multilingual E5 base embedding model optimized for semantic similarity and retrieval tasks. Supports OpenVINO and ONNX inference formats. Ideal for cross-lingual vector search and semantic matching.
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Repository: localaiLicense: apache-2.0
This sentence-transformers model maps text to 384-dimensional dense vectors for semantic similarity tasks. Based on the MiniLM architecture, it is optimized for OpenVINO inference. Ideal for retrieval-augmented generation (RAG) pipelines.
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