Avatarify is a cool project that lets you create a relatively realistic avatar that you can use during video meetings. It works by creating a fake video input device and passing your video input through a neural network in PyTorch. My laptop doesn’t have a GPU, so I used the server/client setup. setting up the server Be sure you’ve installed the Nvidia Docker runtime so that the Docker container can use the GPU.

I host several services on an Alienware gaming computer I keep at my apartment. (We call it the spaceship.) I originally got the computer so I could have a computer with a GPU for machine learning projects, but I’ve since started using this computer to host a bunch of different services. Here I’ve documented how I set up the server. operating system To keep things simple I use Ubuntu 20.04 LTS.

This is how I set up my headless home server with a Jupyter Lab Docker container with an Nvidia GPU runtime. Login is handled by a GitHub OAuth application. Nvidia drivers and the container runtime First, check here (replacing the CUDA version in the URL with your own) to see which Nvidia drivers you need for the CUDA toolkit version you want. I’m using CUDA 11.4.2, which means I need at least driver version 470.

This guide shows how to host multiple Minecraft servers on a single machine with docker-compose. mkdir minecraft_server cd minecraft_server mkdir data/ wget https://kylrth.com/post/minecraft/docker-compose.yml \ -O docker-compose.yml This docker-compose setup uses itzg’s Docker image, which you see further documentation for here. If you’re moving from a vanilla Minecraft world, do the following to get the different world directories in the right position: cp -r ${OLD}/world data/server/world mkdir data/server/world_{nether,the_end} mv data/server/world/DIM-1 data/server/world_nether/DIM-1 mv data/server/world/DIM1 data/server/world_the_end/DIM1 Here’s the map from vanilla Minecraft directories to Spigot directories (which is what itzg’s container uses):

This is how I set up my own Matrix server on a Raspberry Pi with Docker. Unfortunately, the Matrix community has stopped releasing ARM images, so the latest version that will work on ARM is v1.26.0. These instructions will work the same for x86_64 systems, except you’ll be able to use the default x86_64 images in the docker-compose file. This installation comes with Maubot and matrix-registration containers too. If you don’t want to use those features, leave out those sections of the docker-compose config and don’t follow the instructions in the corresponding sections.