Source: https://www.leowkahman.com/2016/03/19/disable-ipv6-raspberry-raspbian/
Firstly, check for presence of IPv6 using ifconfig. You should be seeing a few lines containing inet6 addr: ....
To disable, edit a file: sudo nano /etc/sysctl.conf
Add the following line:
net.ipv6.conf.all.disable_ipv6 = 1
Fonte: http://brandon.invergo.net/news/2012-05-26-using-gnu-stow-to-manage-your-dotfiles.html?round=two
I accidentally stumbled upon something yesterday that I felt like sharing, which fell squarely into the "why the hell didn't I know about this before?" category. In this post, I'll describe how to manage the various configuration files in your GNU/Linux home directory (aka "dotfiles" like .bashrc) using GNU Stow.
The difficulty is that it would be helpful to manage one's configuration files with a version control system like Git, Mercurial or Bazaar, but many/most dotfiles reside at the top-level of your home directory, where it wouldn't be a good idea to initialize a VCS repository. Over time I've come across various programs which aim to manage this for you by keeping all the files in a subdirectory and then installing or linking them into their appropriate places. None of those programs ever really appealed to me. They would require a ton of dependencies (like Ruby and a ton of libraries for it) or t
Based on https://davecoyle.com/tech-notes/ssh-keys-on-a-yubikey-mac/
Install the YubiKey Manager CLI (ykman); alternative installation options can be found here:
brew install ykman
Install GPG >= 2.1. Version 2.1 simplified the running of gpg-agent. The version isn’t a hard requirement, but it might make your life easier.
Source: https://stackoverflow.com/a/45971167/481690
set -a
. ./env.txt
set +a
If env.txt is like:
sudo apt install tensorflow-cuda-latestsudo apt install system76-cuda-latestbash Miniconda3-latest-Linux-x86_64.sh
It is loaded by default by /Library/LaunchAgents/com.adobe.AdobeCreativeCloud.plist.
If you run
launchctl unload -w /Library/LaunchAgents/com.adobe.AdobeCreativeCloud.plist
| # Requirements: | |
| # - active google cloud project | |
| # - enable 'Cloud Text-to-Speech API' | |
| # - GOOGLE_APPLICATION_CREDENTIALS defined as an environment variable, pointing to your JSON account key file | |
| # - Google Cloud SDK installed and initialized | |
| # Based on official quickstart example: https://cloud.google.com/text-to-speech/docs/quickstart-protocol | |
| $dialogue = Read-Host -Prompt 'Dialogue text' | |
| $outputName = Read-Host -Prompt 'Output file name (.mp3 extension will be added automatically)' |
Source: pop-os/tensorman#10 (comment)
When launching a container, be sure to supply the port mappings argument to map the port from the container to the host.
tensorman run -p 8888:8888 --gpu --python3 --jupyter bash
Within the container, you may start the Jupyter notebook with
switch into root: sudo su
list disks and partitions: fdisk -l
find main list filesystem partition and efi partition
create mountpoint: mkdir /mnt/arch
mount partition (additional argument needed for btrfs): mount -t auto -o subvol=@ /dev/nvme0n1p6 /mnt/arch/
(source: https://forum.endeavouros.com/t/chroot-into-a-btrfs-uefi-system-from-live-media/15986/3)
change root into mounted partition: arch-chroot /mnt/arch
mount EFI partition: mount -t auto /dev/nvme0n1p2 /efi/