This repository contains training, generation and utility scripts for Stable Diffusion.
For easier use (GUI and PowerShell scripts etc...), please visit the repository maintained by bmaltais. Thanks to @bmaltais!
This repository contains the scripts for:
- DreamBooth training, including U-Net and Text Encoder
- fine-tuning (native training), including U-Net and Text Encoder
- image generation
- model conversion (supports 1.x and 2.x, Stable Diffision ckpt/safetensors and Diffusers)
These files do not contain requirements for PyTorch and Diffusers. Because the versions of them depend on your environment. Please install PyTorch at first, then Diffusers.
The scripts are tested with PyTorch 1.12.1 and 1.13.0, Diffusers 0.10.2.
All documents are in Japanese currently, and CUI based.
- Environment setup and DreamBooth training guide
- Fine-tuning step-by-step guide: Including BLIP captioning and tagging by DeepDanbooru or WD14 tagger
- Image generation
- Model conversion
Python 3.10.6 and Git:
- Python 3.10.6: https://www.python.org/ftp/python/3.10.6/python-3.10.6-amd64.exe
- git: https://git-scm.com/download/win
Give unrestricted script access to powershell so venv can work:
- Open an administrator powershell window
- Type
Set-ExecutionPolicy Unrestricted
and answer A - Close admin powershell window
Open a regular Powershell terminal and type the following inside:
git clone https://github.com/kohya-ss/sd-scripts.git
cd sd-scripts
python -m venv --system-site-packages venv
.\venv\Scripts\activate
pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116
pip install --upgrade -r requirements_db_finetune.txt
pip install -U -I --no-deps https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl
cp .\bitsandbytes_windows\*.dll .\venv\Lib\site-packages\bitsandbytes\
cp .\bitsandbytes_windows\cextension.py .\venv\Lib\site-packages\bitsandbytes\cextension.py
cp .\bitsandbytes_windows\main.py .\venv\Lib\site-packages\bitsandbytes\cuda_setup\main.py
accelerate config
Answers to accelerate config:
- 0
- 0
- NO
- NO
- All
- fp16
When a new release comes out you can upgrade your repo with the following command:
cd kohya_diffusers_fine_tuning
git pull
.\venv\Scripts\activate
pip install --upgrade -r <requirement file name>
Once the commands have completed successfully you should be ready to use the new version.