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Go library for in-process vector search and embeddings with llama.cpp
Go library for embedded vector search and semantic embeddings using llama.cpp - kelindar/search
This library was created to provide an easy and efficient solution for embedding and vector search, making it perfect for small to medium-scale projects that still need some serious semantic power. It’s built around a simple idea: if your dataset is small enough, you can achieve accurate results with brute-force techniques, and with some smart optimizations like SIMD, you can keep things fast and lean. The library’s strength lies in its simplicity and support for GGUF BERT models, letting you leverage sophisticated embeddings without getting bogged down by the complexities of traditional search systems.
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