faiss

工具介绍

一个用于高效相似性搜索和集聚密集向量的库.

核心特点

• •search time
• •search quality
• •memory used per index vector
• •training time
• •adding time
• •need for external data for unsupervised training
• •the full documentation can be found on the wiki page, including a tutorial, a FAQ and a troubleshooting section
• •the doxygen documentation gives per-class information extracted from code comments
• •to reproduce results from our research papers, Polysemous codes and Billion-scale similarity search with GPUs, refer to the benchmarks README. For [
• •Hervé Jégou initiated the Faiss project and wrote its first implementation