stable-diffusion-intel-mac
stable-diffusion-rocm
| stable-diffusion-intel-mac | stable-diffusion-rocm | |
|---|---|---|
| 1 | 5 | |
| 109 | 57 | |
| - | - | |
| 10.0 | 0.0 | |
| over 1 year ago | over 1 year ago | |
| Jupyter Notebook | Dockerfile | |
| GNU General Public License v3.0 or later | - |
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stable-diffusion-intel-mac
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Run Stable Diffusion on Your M1 Mac’s GPU
Comment from github: "By the way, i confirmed to work on my Intel 16-in MacBook Pro via mps. GPU (Radeon Pro 5500M 8GB) usage is 70-80% and It takes 3 min where --n_samples 1 --n_iter 1. My repo https://github.com/cruller0704/stable-diffusion-intel-mac"
stable-diffusion-rocm
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[D] About the current state of ROCm
Re: stable diffusion https://github.com/AshleyYakeley/stable-diffusion-rocm
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It's time to upscale FSR 2 even further: Meet FSR 2.1
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/...
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Running Stable Diffusion on Your GPU with Less Than 10Gb of VRAM
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.
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Run Stable Diffusion on Your M1 Mac’s GPU
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
- Dockerfile for easy use on an AMD GPU
What are some alternatives?
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
stable-diffusion
invisible-watermark - python library for invisible image watermark (blind image watermark)
stable_diffusion.openvino
sd-webui-colab - A repo for the maintenance of the Colab version of stable-diffusion-webui repo
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
stable-diffusion
3d-ken-burns - an implementation of 3D Ken Burns Effect from a Single Image using PyTorch
stable-diffusion
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM