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A library for efficient similarity search and clustering of dense vectors

Project description

Unofficial prebuilt binary for Linux and MacOS

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-1.5.3-cp37-cp37m-manylinux1_x86_64.whl (4.7 MB view hashes)

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faiss-1.5.3-cp37-cp37m-macosx_10_13_x86_64.whl (1.1 MB view hashes)

Uploaded CPython 3.7m macOS 10.13+ x86-64

faiss-1.5.3-cp36-cp36m-manylinux1_x86_64.whl (4.7 MB view hashes)

Uploaded CPython 3.6m

faiss-1.5.3-cp36-cp36m-macosx_10_13_x86_64.whl (1.1 MB view hashes)

Uploaded CPython 3.6m macOS 10.13+ x86-64

faiss-1.5.3-cp35-cp35m-manylinux1_x86_64.whl (4.7 MB view hashes)

Uploaded CPython 3.5m

faiss-1.5.3-cp35-cp35m-macosx_10_13_x86_64.whl (1.1 MB view hashes)

Uploaded CPython 3.5m macOS 10.13+ x86-64

faiss-1.5.3-cp27-cp27mu-manylinux1_x86_64.whl (4.7 MB view hashes)

Uploaded CPython 2.7mu

faiss-1.5.3-cp27-cp27m-macosx_10_13_x86_64.whl (1.1 MB view hashes)

Uploaded CPython 2.7m macOS 10.13+ x86-64

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