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If you have over 4MB VRAM you can run it locally. I've been experimenting recently and find that even with 10MB VRAM I can only get 256x256 resolution images. I have a Dockerfile I can share that packages up the install process and removes censorship if anyone is interested. I find the censoring is extremely conservative.

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Huh, I've been using the docker container by cmd2 and been doing 512x512 just fine with 8GB. Are you on Windows by any chance?

Yes, windows with a RTX 2070 Super. The logs say the app is trying allocate just a few hundred MB more than what I have. I'm reasonably happy with 256x256 for now, just messing around.

Please do share. I did the same and have it but having trouble deploying it to a prod GPU server, still figuring it out.

Here you go: https://gist.github.com/gvbl/9231406c54e7c9fd37abdfa6c697fe5...

You can run it with a command like this (I'm on windows): docker run -it -v <model file path>:/stable-diffusion/models/ldm/stable-diffusion-v1/model.ckpt -v <outputs folder>:/stable-diffusion/outputs -v <inputs folder>:/stable-diffusion/inputs -v <cache folder>:/root/.cache --gpus all knightley python /stable-diffusion/scripts/txt2img.py --W 256 --H 256 --prompt "a horse wearing a top hat"

assuming you build the image and tag it "knightley"

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