stable-diffusion-rocm
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stable-diffusion-rocm | stable_diffusion.openvino | |
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5 | 47 | |
57 | 1,525 | |
- | - | |
0.0 | 0.8 | |
about 1 year ago | 7 months ago | |
Dockerfile | Python | |
- | Apache License 2.0 |
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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
stable_diffusion.openvino
- FLaNK Stack 05 Feb 2024
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Installing A1111 Stable Diffusion Error
it might be the --xformers flag, try getting rid of that since your not using cuda you wouldn't be able to run it with xformers and you could also try --use-cpu all ... you can also check this out .. https://github.com/bes-dev/stable_diffusion.openvino .. it's probably your best option if your using CPU, which if your PC Graphics are using Intel UHD 620 then you don't have a GPU and an optimized CPU inference would be best to run
- 4 Reasons to Switch to Intel Arc GPUs
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why is SD not actually using the GPU?
SD can be run on a CPU without a GPU. I know for certain it can be done with OpenVINO. In fact, on some i7s, it will run at around 3 seconds per iteration. There was a reddit SD thread a while back saying it can be done with Automatic111. Also, soe recent threads on problems with AMD GPUs suggest Automatic1111 is using the CPU rather than the intended GPU. (Fortuanely, I have a GPU, so I don't have to deal with it myself!)
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Slow Performance on RX 6800 XT; Am I Doing Something Wrong or is ROCm Just this Slow?
I'm not actually entirely convinced that it's even using the GPU. Radeontop shows 0% utilization while the images are generating. Additionally, the listed iteration speed should be impossibly slow for any GPU; it says 26.58s/it, which is slower than just running on a CPU.
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How can i fix it?
iGPU's are in short not supported. There's this repo that may or may not help you, but even if it did I wouldn't expect much.
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Stable Diffusion Web UI for Intel Arc
You can also run it in windows native with openvino, there is a barebones webui for it as well in one of the forks.Requires setting cpu to gpu in one the files. https://github.com/bes-dev/stable_diffusion.openvino
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Intel Arc A770 is underperforming in Tom's Hardware Review
In https://github.com/bes-dev/stable_diffusion.openvino/blob/master/stable_diffusion_engine.py
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So a new benchmark was done for Stable Diffusion on GPU's
" We ended up using three different Stable Diffusion projects for our testing, mostly because no single package worked on every GPU. For Nvidia, we opted for Automatic 1111's webui version(opens in new tab). AMD GPUs were tested using Nod.ai's Shark version(opens in new tab), while for Intel's Arc GPUs we used Stable Diffusion OpenVINO(opens in new tab). "
- Anyone here using Mac?
What are some alternatives?
stable-diffusion
stable-diffusion
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
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
diffusionbee-stable-diffusion-ui - Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. Comes with a one-click installer. No dependencies or technical knowledge needed.
stable-diffusion - A latent text-to-image diffusion model
invisible-watermark - python library for invisible image watermark (blind image watermark)
stable-diffusion-webui-ipex-arc - A guide to Intel Arc-enabled (maybe) version of @AUTOMATIC1111/stable-diffusion-webui