stable_diffusion.openvino VS stable-diffusion

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

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!)

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.

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.

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

In https://github.com/bes-dev/stable_diffusion.openvino/blob/master/stable_diffusion_engine.py

" 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). "

No, sorry, but there's a whole bunch of one-click things now, I think?

I'm running it on Windows 10 using (a modified version of) https://github.com/bfirsh/stable-diffusion.git and Anaconda to create the environment from their `environment.yaml` (all of which was done using the normal `cmd` shell). Then to use it, I activate that env from `cmd` and switch into cygwin `bash` to run the `txt2img.py` script (because it's easier to script, etc.)

I am using the bfirsh version. And yes, I run "pyhthon scripts/txt2imp.py" to generate an image.

Specifically regarding the first option above, I see that the procedure clones the repository from: https://github.com/bfirsh/stable-diffusion.git

Just done a run on my 3080 under Windows using https://github.com/bfirsh/stable-diffusion.git and it's about 8 iterations/sec when nothing else is using CPU or GPU.

I've cloned this repository on my M1 Mac: https://github.com/bfirsh/stable-diffusion/tree/apple-silicon-mps-support

Boom - nice. Here's a fork with that: https://github.com/bfirsh/stable-diffusion/tree/lstein

Requirements are "requirements-mac.txt" which'll need subbing in the guide.

We're testing this out with a few people in Discord before shipping to the blog post.