faiss
Library for efficient similarity search and clustering of dense vectors
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 — installed here under USE=python via SWIG-generated bindings. The PyPI distribution is named "faiss-cpu"; the Python import name is plain "faiss".
homepage ↗homepage ↗ github: facebookresearch/faiss pypi: faiss-cpu
Available in
| Overlay | Newest | Ebuilds | Last activity | |
|---|---|---|---|---|
| stuff GitHub ↗ | 1.14.3 | 3 | 2 d | details › |
Versions & arches
Use flags of 1.14.3
- python Build the SWIG-generated Python bindings (import faiss)
- test Enable dependencies and/or preparations necessary to run tests (usually controlled by FEATURES=test but can be toggled independently)
2 expansion flags (python targets, ABIs, cpu flags…)
- cpu_flags_x86_avx2
- cpu_flags_x86_avx512f