AI & ML Workloads: GPU and Fooocus

Table of Contents

Introduction

We show how to use a ThreeFold GPU node on the grid to deploy AI workloads for graphics and image generation. We will be using Fooocus and a full virtual machine with a GPU card.

Prerequisites

Prepare the System

  • Update the system 
    dpkg --add-architecture i386
apt-get update
apt-get dist-upgrade
reboot
  • Check the GPU info 
    lspci | grep VGA
lshw -c video

Install the GPU Driver

  • Download the latest Nvidia driver
    • Check which driver is recommended 
      apt install ubuntu-drivers-common
ubuntu-drivers devices
    • Install the recommended driver (e.g. with 535) 
      apt install nvidia-driver-535
  • Check the GPU status 
    nvidia-smi

Now that the GPU node is set, let's install and launch Fooocus.

Install the Prerequisites and Launch Fooocus

We install the prerequisites, including Miniconda, clone the repository, download the models and launch Fooocus.

  • Install the prerequisites 
    apt update
apt install python3-pip python3-dev
pip3 install --upgrade pip
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
  • Reload the shell to enable Conda
  • Clone the Fooocus directory and install the Python requirements with Miniconda 
    git clone https://github.com/lllyasviel/Fooocus.git
cd Fooocus
conda env create -f environment.yaml
conda activate fooocus
pip install -r requirements_versions.txt
  • Download the models with conda and deploy Fooocus 
    conda activate fooocus
python entry_with_update.py
  • Create an SSH tunnel to the VM 
    ssh -4 -L 7865:127.0.0.1:7865 root@10.20.4.2

Use Fooocus

You can then access Fooocus:

127.0.0.1:7865

Here are some image generated with Fooocus:

Last change: 2024-08-09