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Comment by prophesi | Hacker News Reader

There's also a fork that requires a lot less VRAM. I was able to get this working with an Nvidia GTX 1070.

https://github.com/basujindal/stable-diffusion

You'd clone the fork, then download Stability AI's checkpoint, sd-v1-4.ckpt, from https://huggingface.co/CompVis/stable-diffusion-v-1-4-origin...

Follow the instructions in the forked repo, and you should be good to go in a manner of minutes.

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The only issue I had was WSL 2 was not using my GPU, so obviously it failed. Couldn't get it working on Windows either, failed at installing dependencies. I'm thinking of dual-booting Linux just to try out stable-diffusion.

I normally dev on Linux but don't do GPU work, only my Windows gaming PC has the horsepower to run stable-diffusion and unfortunately I couldn't get it working on Windows. Shame cause I'd love to play around with it! Does anyone have any tips?

Hm, what issues did you come across on Windows? I have it running on both a Windows PC and a Fedora PC. I uninstalled python, then installed the full installation of Anaconda. Then I followed the "Requirements" section of the readme and I was good to go.

Edit: Just noticed they removed the instructions from the readme for some reason. The requirements section can be found in this diff: https://github.com/basujindal/stable-diffusion/commit/487a0f...

Thanks for the input. I can return with error logs later, but essentially when doing the `conda create env -f environment.yaml` line it would error out partway through. It would download dependencies for a few minutes then fail on one. I tried multiple times and got the same error. I just assumed it was an issue of a dependency not properly supporting windows.

Are you saying you coulda `conda create env -f environment.yaml` fine? This was my first conda install on Windows, so perhaps I missed something else.

Yeah, my Windows machine was able to run that command just fine.

Maybe one of the newer commits broke something? I think I cloned it when b91816301fa62df239a45336b381ee918ff52b2a was the latest, but I'll have to check when I get home.

Yes it works fine for me on Windows with conda.

    conda env create --name envname -f environments.yml

Try reinstalling conda. Do you have a firewall on or anything like that?

Try out a Ubuntu live image. You can probably get set up with everything without even having to touch your HDD! I just don't know how the native NVidia drivers work in that case, but I think you can get them installed and restart the window manager, even w/a a liveCD.

That's a really good idea than finding another HD to install. Thanks.

Same. I've spent a number of nights trying variations on the install instructions. Got the windows CUDA drivers (older graphics card), but no matter what I try, conda, or WSL, pytorch refuses to see the CUDA available.

I'm able to make it works on my GTX 1650 LP. Had to use full precision though or else it generates green images. I also had to reduce the resolution to 320x320 and close every applications that uses vram because the GPU only has 4GB of vram. Took about 2 minutes to generate a single image with ddim sampling steps set to 50.

Does it make images of lesser quality or does it just take longer for the same quality?

Anyone built a Docker image for this? I don't want to duplicate efforts.

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