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RunPod Automatic1111 updater : https://www.patreon.com/posts/1-click-runpod-86438018
WARNING USE THIS INSTALLER HERE : https://www.patreon.com/posts/112099700
USE THIS INSTALLER HERE : https://www.patreon.com/posts/112099700
PREVIOUS INSTALLERS ARE OUTDATED SO USE ABOVE INSTALLER
THIS ABOVE INSTALLER SUPPORTS ALL SD 1.5, SD 3.5, SDXL, FLUX, ETC
For best SD 1.5 Kohya config Click here, and for best SDXL Kohya config Click here
For 8400 (200 repeat) steps training on RunPod, full configuration image : runpod_8400_Steps.png
For Windows only folder paths would change
kohya_installer.sh updated to the latest version
downloadSDXL.sh will now download SDXL FP16 VAE so you don't need --no-half-vae anymore
It will also download SDXL FP32 VAE which you can use during training
chmod +x downloadSDXL.sh
./downloadSDXL.sh
Execute below code 1 time after each restart of the Pod to get super insane speed with A5000 GPU. Same price of RTX 3090. 1.64 IT/s for 1024x1024 full SDLX DreamBooth training
apt update
apt install libcudnn8=8.9.7.29-1+cuda11.8 libcudnn8-dev=8.9.7.29-1+cuda11.8
To use certain GPU if you have multiple GPUs : --gpu_ids=1
Changes : It will auto download Realistic_Vision_V5.1.safetensors and vae-ft-mse-840000-ema-pruned.ckpt (best VAE for SD 1.5 models) and sdxl_vae.safetensors (best VAE for SDXL) into the relative folders in both templates.
Best SDXL LoRA Training Tutorial published 8 August 2023 > Become A Master Of SDXL Training With Kohya SS LoRAs - Combine Power Of Automatic1111 & SDXL LoRAs
downloadSDXL. sh file will automatically download latest models mentioned above
RunPod io link > https://bit.ly/RunPodIO
* Select stable-diffusion:web-ui or stable-diffusion:fast-stable-diffusion templates
* Make container disk size at least 15 GB
Download attached kohya_installer.sh, downloadSDXL.sh and then upload it into your Workspace folder
Or here quick command
chmod +x kohya_installer.sh
./kohya_installer.sh
If you pick stable-diffusion:web-ui template download attached relauncher.py, enter inside stable-diffusion-webui folder, upload relauncher. py. It will ask you to Overwrite so overwrite. Then restart your pod 1 time. This is only necessary 1 time to prevent permanent relaunching of Automatic1111 Web UI.
You can also use this runpodctl auto installer from this Patreon post > https://www.patreon.com/posts/1-click-bat-file-87505171
Screenshot of install commands
Use a custom model otherwise not working.
.e.g : /workspace/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned.ckpt
Use below command to kill Web UI instance to save more VRAM before doing Kohya Training
fuser -k 3000/tcp
Use below command to start Kohya on RunPod after installation
apt update
yes | apt-get install python3.10-tk
fuser -k 7860/tcp
cd /workspace/kohya_ss
source venv/bin/activate
export CUDA_VISIBLE_DEVICES=0
bash gui.sh --share --headless
By changing CUDA_VISIBLE_DEVICES to different CUDA you can start different training on each GPU
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