ROCm-docker
stable-diffusion
ROCm-docker | stable-diffusion | |
---|---|---|
3 | 111 | |
392 | 1,749 | |
1.0% | - | |
5.1 | 10.0 | |
23 days ago | over 1 year ago | |
Shell | Jupyter Notebook | |
MIT License | GNU Affero General Public License v3.0 |
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ROCm-docker
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
https://rocm.docs.amd.com/projects/install-on-linux/en/lates... links to ROCm/ROCm-docker: https://github.com/ROCm/ROCm-docker which is the source of docker.io/rocm/rocm-terminal: https://hub.docker.com/r/rocm/rocm-terminal :
docker run -it --device=/dev/kfd --device=/dev/dri --group-add video rocm/rocm-terminal
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Stable Diffusion PR optimizes VRAM, generate 576x1280 images with 6 GB VRAM
Not sure about the 6600, but there is a guide for Linux at least:
https://m.youtube.com/watch?v=d_CgaHyA_n4&feature=emb_logo
And this is somehow relevant (possibly), as I kept the link open.
https://github.com/RadeonOpenCompute/ROCm-docker/issues/38
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It's working perfectly under Linux
As for the Docker image, I suppose you could compile the image (https://hub.docker.com/r/rocm/pytorch) by yourself using the sources (https://github.com/RadeonOpenCompute/ROCm-docker#building-images), which seems to be quite a bit of work. Better, you could just use an older tag of the upstream image, eg. rocm4.1.1_ubuntu18.04_py3.6_pytorch instead of rocm4.2_ubuntu18.04_py3.6_caffe2 or latest . Just make sure your container version matches your host ROCm version.
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?
awesome-kubernetes - A curated list for awesome kubernetes sources :ship::tada:
diffusers-uncensored - Uncensored fork of diffusers
AiDungeon2-Docker-ROCm - Runs an AIDungeon2 fork in Docker on AMD ROCm hardware.
stable-diffusion-krita-plugin
ZLUDA - CUDA on AMD GPUs
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
stable-diffusion - Go to lstein/stable-diffusion for all the best stuff and a stable release. This repository is my testing ground and it's very likely that I've done something that will break it.
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
docker-elk - The Elastic stack (ELK) powered by Docker and Compose.
stable_diffusion.openvino
Dokku - A docker-powered PaaS that helps you build and manage the lifecycle of applications
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]