rocm-build
rocm-build | stable_diffusion.openvino | |
---|---|---|
7 | 47 | |
168 | 1,525 | |
- | - | |
0.0 | 0.8 | |
4 months ago | 7 months ago | |
C++ | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
rocm-build
- AMD's Hidden $100 Stable Diffusion Beast!
-
AMD GPU driver not installed correctly
Scripts to help with building rocm and hip. It will also help work out dependencies. You will need to modify the scripts for them to work and not all are required. https://github.com/xuhuisheng/rocm-build
-
Stable Diffusion on AMD RDNA3
Short answer no. Long answer "in theory" yes. I tried this [1] but gave up as building rocm + deps takes up to 6h :/ Official statement [2]
[1] https://github.com/xuhuisheng/rocm-build
-
Show HN: InvokeAI, an open source Stable Diffusion toolkit and WebUI
I am in the same boat with a gfx03 card. What patch did you use? The ones here? https://github.com/xuhuisheng/rocm-build
I also tried to compile pytorch with its Vulkan backend, but ended throwing the towel as LDFLAGS are a mess to get right (I successfully compiled it, but that was only part of the build chain, and decided I had better things to spend time on). I wonder how that would perform; ncnn works pretty decently.
-
How do I run Stable Diffusion and sharing FAQs
Unofficial black magic is available: https://github.com/xuhuisheng/rocm-build/tree/master/navi10 (pytorch 1.12.0 is outdated but can run SD)
- Deep Learning options on Radeon RX 6800
-
Which version of ROCm and Tensorflow should I use?
also have an RX570, currently running latest Tensorflow and ROCm 4.1. had to recompile some parts of ROCm 4.1 libraries to get tensorflow to work. mostly followed this guide: https://github.com/xuhuisheng/rocm-build/tree/master/gfx803
stable_diffusion.openvino
- FLaNK Stack 05 Feb 2024
-
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
-
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!)
-
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.
-
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.
-
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
-
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
-
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-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
stable-diffusion
stable-diffusion-webui - Stable Diffusion web UI
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.
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
stable-diffusion
tensorflow-upstream - TensorFlow ROCm port
stable-diffusion-rocm
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-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]
stable-diffusion - A latent text-to-image diffusion model