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ONNX implementation of the BGE-M3 multilingual embedding model and tokenizer with native C#, Java, and Python implementations. Generates all three embedding types: dense, sparse, and ColBERT vectors.
A demonstration of hybrid search with reranking using Qdrant and BGE-M3 model. A showcase of dense and sparse retrieval combined with ColBERT reranking for optimal search results
Does a TypeSafe Jev rerank beat embedding search? Graded relevance eval (9,831 pairs, 164 zh/en queries) over the Agent Skills Hub catalog, with the judge-circularity bias measured.
RAG for researchers: page-level citations from your personal library, LLM access via MCP. Ask your entire archive, get answers with the intelligence of leading AI.
Local SQL archive for your Super Whisper dictation history. Thin sqlite3 wrapper + multilingual semantic search via bge-m3 / Ollama. macOS, distributed via Homebrew.
Citation Oracle ✦ — an AI oracle for a PhD literature corpus: neural (bge-m3) semantic search + an interactive citation constellation, plus MIT-licensed Claude Code skills incl. a Gemini Deep Research prompt builder