StableDiffusion-WSL

== https://github.com/ShivamShrirao/diffusers/tree/main/examples/dreambooth ==

* Make a place for downloads
mkdir Downloads
cd Downloads

* Download & Install Anaconda
wget https://repo.anaconda.com/archive/Anaconda3-2022.05-Linux-x86_64.sh
chmod +x ./Anaconda3-2022.05-Linux-x86_64.sh
./Anaconda3-2022.05-Linux-x86_64.sh

* Nvidia CUDA toolkit for Ubuntu WSL - https://developer.nvidia.com/cuda-downloads
wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/11.7.1/local_installers/cuda-repo-wsl-ubuntu-11-7-local_11.7.1-1_amd64.deb
sudo dpkg -i cuda-repo-wsl-ubuntu-11-7-local_11.7.1-1_amd64.deb
sudo cp /var/cuda-repo-wsl-ubuntu-11-7-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda

* New shell with Anaconda & install g++
bash
sudo apt install build-essential

* New virtual Python environment
conda update -n base -c defaults conda
conda create --name diffusers python=3.9
conda activate diffusers

* Make a directory for all your github downloads, then download diffusers
mkdir ~/github
cd ~/github
git clone https://github.com/ShivamShrirao/diffusers.git
cd diffusers

* Install required packages
pip install .
cd examples/dreambooth
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
pip install -r requirements.txt
pip install -U --pre triton
pip install ninja bitsandbytes
pip install git+https://github.com/facebookresearch/xformers@1d31a3a#egg=xformers

* Configure / login
accelerate config
huggingface-cli login
mkdir -p training
mkdir -p classes
explorer.exe .

* Edit your training file and add this line to the top or reboot:
export LD_LIBRARY_PATH=/usr/lib/wsl/lib:$LD_LIBRARY_PATH

* Copy your training file from your Windows desktop (or wherever you saved it):
cp /mnt/c/Users/YOUR_USERNAME/Desktop/my_training.sh ./
chmod +x ./my_training.sh
./my_training.sh


* NB: If you get an error like this -
403 Client Error: Forbidden for url: https://huggingface.co/CompVis/stable-diffusion-v1-4/resolve/main/model_index.json

Then:
Make sure you've visited https://huggingface.co/CompVis/stable-diffusion-v1-4 and accepted the licence!
NB. If this is the very first time you've used diffusers, it's about a 6GB download

To train again next time, simply:

* Start Ubuntu, then:
conda activate diffusers
cd ~/github/diffusers/examples/dreambooth
./my_training.sh