StableDiffusion/KohyaSS
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bmaltais 2022-12-04 21:22:57 -05:00 committed by GitHub
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@ -21,20 +21,29 @@ Give unrestricted script access to powershell so venv can work:
Open a regular Powershell terminal and type the following inside:
```powershell
# Clone the Kohya_ss repository
git clone https://github.com/bmaltais/kohya_ss.git
# Navigate to the newly cloned directory
cd kohya_ss
# Create a virtual environment using the system-site-packages option
python -m venv --system-site-packages venv
# Activate the virtual environment
.\venv\Scripts\activate
# Install the required packages
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.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
# Copy the necessary files to the virtual environment's site-packages directory
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
# Configure the accelerate utility
accelerate config
```
@ -396,4 +405,4 @@ options:
- The data format of checkpoint at the time of saving can be specified with the --save_precision option. You can choose float, fp16, and bf16.
- Added a --save_state option to save the learning state (optimizer, etc.) in the middle. It can be resumed with the --resume option.
* 11/9 (v8): supports Diffusers 0.7.2. To upgrade diffusers run `pip install --upgrade diffusers[torch]`
* 11/7 (v7): Text Encoder supports checkpoint files in different storage formats (it is converted at the time of import, so export will be in normal format). Changed the average value of EPOCH loss to output to the screen. Added a function to save epoch and global step in checkpoint in SD format (add values if there is existing data). The reg_data_dir option is enabled during fine tuning (fine tuning while mixing regularized images). Added dataset_repeats option that is valid for fine tuning (specified when the number of teacher images is small and the epoch is extremely short).
* 11/7 (v7): Text Encoder supports checkpoint files in different storage formats (it is converted at the time of import, so export will be in normal format). Changed the average value of EPOCH loss to output to the screen. Added a function to save epoch and global step in checkpoint in SD format (add values if there is existing data). The reg_data_dir option is enabled during fine tuning (fine tuning while mixing regularized images). Added dataset_repeats option that is valid for fine tuning (specified when the number of teacher images is small and the epoch is extremely short).