facebookresearch/faiss
A library for efficient similarity search and clustering of dense vectors.
Builder
Meta Research
facebookresearch • ai-lab
Stars
40,163
Using upstream star count
Forks
4,398
Using upstream fork count
Open Issues
0
Activity Score
0/100
0 commits in 30d
Created
Feb 7, 2017
Project creation date
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed primarily at Meta's [Fundamental AI Research](https://ai.facebook.com/) group.
Unmapped
AI Trends
category
Deployment Context
Skill Areas
Updated 2 months ago
7 Days
0
30 Days
0
90 Days
20
pgvector cosine similarity · $0
Loading…