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A library for efficient similarity search and clustering of dense vectors

Project description

*Unofficial prebuilt binary*

The repo that builds this project can be found here: https://github.com/onfido/faiss_prebuilt

Original readme:

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.


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faiss_prebuilt-1.4-py2-none-macosx_10_12_x86_64.whl (912.9 kB) Copy SHA256 hash SHA256 Wheel py2
faiss_prebuilt-1.4-py2-none-macosx_10_13_x86_64.whl (912.9 kB) Copy SHA256 hash SHA256 Wheel py2
faiss_prebuilt-1.4-py2-none-manylinux1_x86_64.whl (3.6 MB) Copy SHA256 hash SHA256 Wheel py2
faiss_prebuilt-1.4-py3-none-macosx_10_12_x86_64.whl (898.7 kB) Copy SHA256 hash SHA256 Wheel py3
faiss_prebuilt-1.4-py3-none-macosx_10_13_x86_64.whl (898.7 kB) Copy SHA256 hash SHA256 Wheel py3
faiss_prebuilt-1.4-py3-none-manylinux1_x86_64.whl (3.6 MB) Copy SHA256 hash SHA256 Wheel py3

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