sd-webui-colab VS stable-diffusion-rocm

(Added Aug. 28, 2022) Colab notebook Stable Diffusion WebUi - Altryne by altryne. GitHub repo. txt2img. img2img. inpainting. Gradio user interface. Uses sd-webui repo.

you can try the colab version of hlky repo: https://github.com/altryne/sd-webui-colab, easier to setup or a one cell colab version: https://github.com/pinilpypinilpy/sd-webui-colab-simplified, everything works in one cell

For those without GPU's / not a powerful enough one. You can start the hlky stable diffusion webui (yes, web ui) in Google Colab with this notebook[0].

It's simple and it works, using colab for processing but actually giving you a URL (ngrok-style) to open the pretty web ui in your browser.

I've been using that on-the-go when not at my PC and it's been working very well for me (after trying numerous other colab-dedicated repos, trying to fix them, and failing).

[0]: https://github.com/altryne/sd-webui-colab

The code is directly adapted from the Colab notebook repo based on the hlky GitHub repo. I really don't have much experience with coding and didn't change much of the code other than the paths specific to Kaggle.

I'm running SD-webui on google colab https://github.com/altryne/sd-webui-colab/ with a colab pro account and its awesome but it does crash with attempting larger images. Is anyone using a google colab pro+ account and able to process larger images?

Based off of https://github.com/altryne/sd-webui-colab and https://github.com/hlky/stable-diffusion

Re: stable diffusion https://github.com/AshleyYakeley/stable-diffusion-rocm

Very easy actually. This is not officially documented, but with a recent enough kernel you don't have to install anything. You can grab the official rocm container and it'll just work. For example for Stable Diffusion see https://github.com/AshleyYakeley/stable-diffusion-rocm/blob/...

I had good luck with these directions, which let you run inside a docker container:

https://github.com/AshleyYakeley/stable-diffusion-rocm

I had to make the one line change suggested in issue #3 to get it to run under 8GB.

radeontop suggests 4GB might work.

I also had to add this environment variable to make it work on my unsupported radeon 6600xt:

HSA_OVERRIDE_GFX_VERSION=10.3.0

It takes under two minutes per batch of 5 images with the --turbo option.

(Base OS is manjaro; using the distro's version of docker; not the flatpack docker package.)

If you don't have a GPU, paperspace will rent you an appropriate VM.

I have it working on an RX 6800, used the scripts from this repo[0] to build a docker image that has ROCm drivers and PyTorch installed.

I'm running Ubuntu 22.04 LTS as the host OS, didn't have to touch anything beyond the basic Docker install. Next step is build a new Dockerfile that adds in the Stable Diffusion WebUI.[1]

[0] https://github.com/AshleyYakeley/stable-diffusion-rocm