Metadata-Version: 2.4
Name: faiss
Version: 1.7.3
Summary: A library for efficient similarity search and clustering of dense vectors
Home-page: https://github.com/facebookresearch/faiss
Author: Matthijs Douze, Jeff Johnson, Herve Jegou, Lucas Hosseini
Author-email: matthijs@fb.com
License: MIT
Keywords: search nearest neighbors
Requires-Dist: numpy
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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 by Facebook AI Research.
