Result for 0D2B28CCD86FC2109D8BF19D2D182668C98507D0

Query result

Key Value
FileName./usr/lib/x86_64-linux-gnu/cmake/faiss/faiss-targets-none.cmake
FileSize815
MD53C6A3F8C0A9FE8E7351673E50E4C9843
SHA-10D2B28CCD86FC2109D8BF19D2D182668C98507D0
SHA-256E05BE0631890CD0C6EC3499C94D5AFBDBAE8AA562F2E68598B60CEB1DB042EDC
SSDEEP12:x3mcq86bVZdY0B2pnJRWDUVYAuVBAtjDHHiI0RAgTKMpyBAMOMf2ZyMLyBFUL2mp:x3m7hK0qUMYAsMiI0RAwQHNuLWajUu
TLSHT1AE019E230F959C9743E1FF63B9C66244D271CAF35F857D695B06276912F0929060F04E
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize1044092
MD570FC79FFB4C4604F046042050FE4693D
PackageDescriptionefficient 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/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. . This package contains the CPU-only version of the development files.
PackageMaintainerDebian Deep Learning Team <debian-ai@lists.debian.org>
PackageNamelibfaiss-dev
PackageSectionlibdevel
PackageVersion1.7.3-2+b1
SHA-185993B7FD3BFFF6955EF84D0B0A5AB6392D0F758
SHA-256D55FCF187BF3F264C5E7764BF256E604FCB13D13E1B836BF0B1D7AC6711EDAC6