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stable-diffusion | stable_diffusion.openvino | |
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8 | 47 | |
436 | 1,524 | |
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0.0 | 0.8 | |
12 months ago | 7 months ago | |
Python | ||
GNU General Public License v3.0 or later | Apache License 2.0 |
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stable-diffusion
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DALL·E Now Available Without Waitlist
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.)
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How do I save the arguments for images I create when using the terminal? (Apple M1 Pro)
I am using the bfirsh version. And yes, I run "pyhthon scripts/txt2imp.py" to generate an image.
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Current canonical way to install Stable Diffusion on Apple Silicon?
Specifically regarding the first option above, I see that the procedure clones the repository from: https://github.com/bfirsh/stable-diffusion.git
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One-Click Install Stable Diffusion GUI App for M1 Mac. No Dependencies Needed
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.
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Using the same seed and same prompt is still resulting in two different images?
I've cloned this repository on my M1 Mac: https://github.com/bfirsh/stable-diffusion/tree/apple-silicon-mps-support
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Run Stable Diffusion on Your M1 Mac’s GPU
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.
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?
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.
sd-webui-colab - A repo for the maintenance of the Colab version of stable-diffusion-webui repo
stable-diffusion
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
stable-diffusion-rocm
stable-diffusion - A latent text-to-image diffusion model
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.
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