shrink-vector-store

【数据与研究】Shrink an embedding/RAG vector store 4–32× via int8 or binary quantization with a float rescore pass, preserving recall and provenance metadata. Use when a vector store is too large to be laptop-resident, query cost/latency is too high, or embeddings need to be quantized for FAISS/Qdrant/usearch. Do NOT use for embed-time ingestion failures (e.g. a p…

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