LoRA Ease WSL is a modified Python script of LoRA Ease from multimodalart to run on locally on Windows 10/11 via WSL.
This script combines the Pivotal Tuning technique used on Replicate's SDXL Cog trainer with the Prodigy optimizer used in the Kohya trainer (plus a bunch of other optimizations) to achieve very good results on training Dreambooth LoRAs for SDXL.
multimodalart's blog post on the script:
https://huggingface.co/blog/sdxl_lora_advanced_script
araminta_k's training tutorial:
https://huggingface.co/blog/alvdansen/training-lora-m3lt
v1.1 - Add Apple Metal support.
v1.0 - Init fork and modified to run on Windows WSL.
Install WSL with Ubuntu (Ubuntu 22.04)
wsl --install Ubuntu
You'll be asked to provide a username and password for your Ubuntu install.
You should now be logged into your WSL Ubuntu distro.
Update the system packages:
sudo apt update
sudo apt upgrade
Install Python related stuff:
sudo apt install python-is-python3
sudo apt install python3-pip
Check if your Nvidia video card is recognized:
nvidia-smi
Make sure you are currently in your home directory:
cd $home
pwd
Make a new directory to clone lora ease repo:
mkdir train
Go into dir:
cd train
Clone this repo from Github:
git clone https://github.com/dicksondickson/lora-ease-wsl.git
Go into the dir:
cd lora-ease-wsl
Install lora ease required dependencies:
pip install -r requirements_local.txt
Run the LoRA Ease main python script. This will automatically install other stuff and download required models.
python app.py
After that is done, you should be presented with a link to load up the GUI in your web browser:
Running on local URL: http://127.0.0.1:7860
Have fun!
Thanks to multimodalart for this wonderful script.
Original repo:
https://huggingface.co/spaces/multimodalart/lora-ease
Github version of this repo:
https://github.com/dicksondickson/lora-ease-wsl
Hugging Face version of this repo:
https://huggingface.co/dicksondickson/lora-ease-wsl