How to Install and Uninstall leela-zero Package on Kali Linux
Last updated: December 24,2024
1. Install "leela-zero" package
Learn how to install leela-zero on Kali Linux
$
sudo apt update
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$
sudo apt install
leela-zero
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2. Uninstall "leela-zero" package
Here is a brief guide to show you how to uninstall leela-zero on Kali Linux:
$
sudo apt remove
leela-zero
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the leela-zero package on Kali Linux
Package: leela-zero
Source: leela-zero (0.17-1)
Version: 0.17-1+b3
Installed-Size: 1754
Maintainer: Ximin Luo
Architecture: amd64
Depends: libboost-filesystem1.83.0 (>= 1.83.0), libboost-program-options1.83.0 (>= 1.83.0), libc6 (>= 2.34), libgcc-s1 (>= 3.0), libqt5core5a (>= 5.15.1), libstdc++6 (>= 13.1), ocl-icd-libopencl1 | libopencl1, ocl-icd-libopencl1 (>= 1.0) | libopencl-1.2-1, zlib1g (>= 1:1.1.4)
Recommends: opencl-icd, clinfo
Size: 542388
SHA256: 59f104496834bfd9f8e4bd6de68982b78403f0c1f48909e999850d6ad8d22432
SHA1: 4486f50a9466e984a87575d827edb6e6774c66c2
MD5sum: c9075c0b4a619d49b54b756f4e42c570
Description: Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper
A Go program with no human provided knowledge. Using MCTS (but without Monte
Carlo playouts) and a deep residual convolutional neural network stack.
.
This is a fairly faithful reimplementation of the system described in the
Alpha Go Zero paper "Mastering the Game of Go without Human Knowledge". For
all intents and purposes, it is an open source AlphaGo Zero.
.
https://deepmind.com/documents/119/agz_unformatted_nature.pdf
.
No network weights are in this repository. If you manage to obtain the AlphaGo
Zero weights, this program will be about as strong, provided you also obtain a
few Tensor Processing Units. Lacking those TPUs, the author recommends a top
of the line GPU - it's not exactly the same, but the result would still be an
engine that is far stronger than the top humans.
.
Recomputing the AlphaGo Zero weights will take about 1700 years on commodity
hardware. Upstream is running a public, distributed effort to repeat this
work. Working together, and especially when starting on a smaller scale, it
will take less than 1700 years to get a good network (which you can feed into
this program, suddenly making it strong). To help with this effort, run the
leelaz-autogtp binary provided in this package. The best-known network weights
file is at http://zero.sjeng.org/best-network
Description-md5:
Homepage: https://github.com/gcp/leela-zero
Tag: uitoolkit::qt
Section: games
Priority: optional
Filename: pool/main/l/leela-zero/leela-zero_0.17-1+b3_amd64.deb
Source: leela-zero (0.17-1)
Version: 0.17-1+b3
Installed-Size: 1754
Maintainer: Ximin Luo
Architecture: amd64
Depends: libboost-filesystem1.83.0 (>= 1.83.0), libboost-program-options1.83.0 (>= 1.83.0), libc6 (>= 2.34), libgcc-s1 (>= 3.0), libqt5core5a (>= 5.15.1), libstdc++6 (>= 13.1), ocl-icd-libopencl1 | libopencl1, ocl-icd-libopencl1 (>= 1.0) | libopencl-1.2-1, zlib1g (>= 1:1.1.4)
Recommends: opencl-icd, clinfo
Size: 542388
SHA256: 59f104496834bfd9f8e4bd6de68982b78403f0c1f48909e999850d6ad8d22432
SHA1: 4486f50a9466e984a87575d827edb6e6774c66c2
MD5sum: c9075c0b4a619d49b54b756f4e42c570
Description: Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper
A Go program with no human provided knowledge. Using MCTS (but without Monte
Carlo playouts) and a deep residual convolutional neural network stack.
.
This is a fairly faithful reimplementation of the system described in the
Alpha Go Zero paper "Mastering the Game of Go without Human Knowledge". For
all intents and purposes, it is an open source AlphaGo Zero.
.
https://deepmind.com/documents/119/agz_unformatted_nature.pdf
.
No network weights are in this repository. If you manage to obtain the AlphaGo
Zero weights, this program will be about as strong, provided you also obtain a
few Tensor Processing Units. Lacking those TPUs, the author recommends a top
of the line GPU - it's not exactly the same, but the result would still be an
engine that is far stronger than the top humans.
.
Recomputing the AlphaGo Zero weights will take about 1700 years on commodity
hardware. Upstream is running a public, distributed effort to repeat this
work. Working together, and especially when starting on a smaller scale, it
will take less than 1700 years to get a good network (which you can feed into
this program, suddenly making it strong). To help with this effort, run the
leelaz-autogtp binary provided in this package. The best-known network weights
file is at http://zero.sjeng.org/best-network
Description-md5:
Homepage: https://github.com/gcp/leela-zero
Tag: uitoolkit::qt
Section: games
Priority: optional
Filename: pool/main/l/leela-zero/leela-zero_0.17-1+b3_amd64.deb