stable-diffusion-rocm
stable-diffusion
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stable-diffusion-rocm | stable-diffusion | |
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5 | 111 | |
57 | 1,749 | |
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0.0 | 10.0 | |
about 1 year ago | over 1 year ago | |
Dockerfile | Jupyter Notebook | |
- | GNU Affero General Public License v3.0 |
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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
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PSA: You can run your GPU's at 80% power and get the same rendering speeds while saving heat/fan noise/electricity
use or update this one : https://github.com/hlky/stable-diffusion it has all the samplers, and if you want perfect faces, try k_euler_a
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"a software developer after fixing a bug", by DALL-E 2
try this one https://github.com/hlky/stable-diffusion you need at least a 1050 to run it tho
- Which is the best fork out there ?
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At the end of my rope on hlky fork, can anyone recommend any alternative GUI forks I could switch to?
https://github.com/hlky/stable-diffusion/issues/153 With 36 comments and tons of before and after comparisons, which are now deleted
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CUDA memory error with hlky repo, (4GB Nvidia) - any ideas?
I wanted to try hlky version (https://github.com/hlky/stable-diffusion) , due to the WebUI and integration with upscaling models. It should also have the option to be optimized for low VRAM. To avoid getting a green square I have to add the parameters "--precision full --no-half". When I run a prompt, even with the smallest image size, I immediately get a CUDA memory error. Interestingly, without these parameters there isn't any memory error (but, of course, the result is a green square)
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Fallout 5: Toronto (created with AI)
Made using https://github.com/hlky/stable-diffusion
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Just released a Colab notebook that combines Craiyon+Stable Diffusion
Any chance to get this integrated into something like hlky's web ui?
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AI Tekst til bilde: Elg og stavkirke med nordlys over Norsk flagg i bakgrunnen [OC] Mer detaljer i posten
Linux Guide her. Jeg har også Linux, men jeg valgte å sette det opp på Windows boksen min fordi driverne til Nvidia kortet på Linux ikke er helt sammarbeidsvillig når det kommer til å justere viftene etter sensorene i kortet (så jeg må sette det manuelt).
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Using GFPGAN for only the eyes?
I'm seeing GFPGAN essentially remove all texture from faces, and I only want to use it on the eyes. Any thoughts on how to do this? I am using hlky/stable-diffusion now but I have no issues running a different repo/fork if needed and using command line.
- What's the best install of Stable Diffusion right now?
What are some alternatives?
stable-diffusion
diffusers-uncensored - Uncensored fork of diffusers
stable_diffusion.openvino
stable-diffusion-krita-plugin
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
3d-ken-burns - an implementation of 3D Ken Burns Effect from a Single Image using PyTorch
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
stable-diffusion
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]