How to Install and Uninstall libfaiss-dev Package on Kali Linux
Last updated: May 19,2024
Deprecated! Installation of this package may no longer be supported.
1. Install "libfaiss-dev" package
Please follow the steps below to install libfaiss-dev on Kali Linux
$
sudo apt update
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$
sudo apt install
libfaiss-dev
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2. Uninstall "libfaiss-dev" package
This guide covers the steps necessary to uninstall libfaiss-dev on Kali Linux:
$
sudo apt remove
libfaiss-dev
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the libfaiss-dev package on Kali Linux
Package: libfaiss-dev
Source: faiss
Version: 1.7.4-3
Installed-Size: 8890
Maintainer: Debian Deep Learning Team
Architecture: amd64
Depends: libblas-dev | libblas.so, liblapack-dev | liblapack.so
Size: 1184148
SHA256: a45539776a6915f4c26d7f01235b2f2dc8aeeca04bb3f53450171c869977202a
SHA1: e7b9acd3c8630520d67725b3935f75eb013ac956
MD5sum: 202a58bf79d9aaffcbe113729caa29db
Description: 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/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.
Description-md5:
Multi-Arch: same
Homepage: https://github.com/facebookresearch/faiss
Section: science
Priority: optional
Filename: pool/main/f/faiss/libfaiss-dev_1.7.4-3_amd64.deb
Source: faiss
Version: 1.7.4-3
Installed-Size: 8890
Maintainer: Debian Deep Learning Team
Architecture: amd64
Depends: libblas-dev | libblas.so, liblapack-dev | liblapack.so
Size: 1184148
SHA256: a45539776a6915f4c26d7f01235b2f2dc8aeeca04bb3f53450171c869977202a
SHA1: e7b9acd3c8630520d67725b3935f75eb013ac956
MD5sum: 202a58bf79d9aaffcbe113729caa29db
Description: 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/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.
Description-md5:
Multi-Arch: same
Homepage: https://github.com/facebookresearch/faiss
Section: science
Priority: optional
Filename: pool/main/f/faiss/libfaiss-dev_1.7.4-3_amd64.deb