Implementation of the proposed MaskBit from Bytedance AI
Face search engine: 100% recall at 96x less memory than HNSW. Register photos, identify people from camera/video/images. AVX-512 + Rust. No GPU needed.
🚀 Supercharge your RAG system with binary quantization - Achieve 10x faster retrieval and 32x storage reduction. Complete implementation with Milvus, OpenAI embeddings, and practical examples.
32 Bytes: what Cohere Embed 5's 32-byte binary vectors do without a shortlist. Evaluation code on three ViDoRe v3 sets in six languages, a call-budgeted trial-key client, and a Metal GPU search over binary codes (exact top-100 of 10M codes in 4.45 ms on an M2 MacBook Air).
To associate your repository with the binary-quantization topic, visit your repo's landing page and select "manage topics."