This repository now includes the solutions provided by Kohya_ss in a single location. I have combined both solutions under one repository to align with the new official Kohya repository where he will maintain his code from now on: https://github.com/kohya-ss/sd-scripts.
This step is optional but can improve the learning speed for NVidia 4090 owners...
Due to the filesize I can't host the DLLs needed for CUDNN 8.6 on Github, I strongly advise you download them for a speed boost in sample generation (almost 50% on 4090) you can download them from here: https://b1.thefileditch.ch/mwxKTEtelILoIbMbruuM.zip
To install simply unzip the directory and place the cudnn_windows folder in the root of the kohya_diffusers_fine_tuning repo.
Run the following command to install:
```
python .\tools\cudann_1.8_install.py
```
## Upgrade
When a new release comes out you can upgrade your repo with the following command:
```powershell
cd kohya_ss
git pull
.\venv\Scripts\activate
pip install --upgrade -r requirements.txt
```
Once the commands have completed successfully you should be ready to use the new version.
You can create LoRA network by running the dedicated GUI with:
```
python lora_gui.py
```
or via the all in one GUI:
```
python kahya_gui.py
```
Once you have created the LoRA network you can generate images via auto1111 by installing the extension found here: https://github.com/kohya-ss/sd-webui-additional-networks
