stablediffusion-directml
SHARK
stablediffusion-directml | SHARK | |
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6 | 84 | |
41 | 1,387 | |
- | 1.7% | |
3.6 | 9.4 | |
about 1 year ago | 12 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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stablediffusion-directml
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Automatic1111 for Intel Arc (A380 Tested)
stable-diffusion-stability-ai (Directml version)
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Stable Diffusion on AMD APUs
https://github.com/lshqqytiger/k-diffusion-directml/tree/master --->this will need to be named k-diffusion https://github.com/lshqqytiger/stablediffusion-directml/tree/main ----> this will need to be renamed stable-diffusion-stability-ai
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What am I doing wrong? Inpainting reverts to original...
I'm using the directml fork of the Automatic1111 web gui on my AMD RX 6800 XT , and it seems to work fine with txt2img, but my attempts at inpainting to fix up the faces is getting me nowhere. This isn't the browser issue, in that the faces are being shown as being edited in the preview, but they successively converge on the original bad image that's masked... I've attached a youtube clip of how it goes for me. Help!
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Man I wish I could do all this cool shit too
Download k-diffusion and stablediffusion folders. (click green button "Code" and download as ZIP). Go to the folder you installed in step 1 and browse to repositories, extract these two folders there. Rename them to k-diffusion and stable-diffusion-stability-ai. If you already have these folders delete them first.
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SD made me regret buying an AMD card.
There is couple options, easy one for windows is this fork https://github.com/lshqqytiger/stablediffusion-directml you don't need to convert models to onyxxx is simply a1111 using directml so you can use all features like controlnet, but will be probably slower than shark or linux a1111 with rocm (why the hell is there no rocm for windows :/), tbh If I were you, I'd probably try to sell the card and buy, for example, a 3060 12GB
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Intel Arc Stable difussion?
3) install k-diffusion-directml and stablediffusion-directm under ..\stable-diffusion-webui-arc-directml-master\repositories (tutorial)
SHARK
- Llama 2 on ONNX runs locally
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[D] Confusion over AMD GPU Ai benchmarking
https://github.com/AUTOMATIC1111/stable-diffusion-webui, https://github.com/nod-ai/SHARK, those are the repos for the open source tools mentioned. u/CeFurkan has really nice tutorial videos on YouTube for stable diffusion. Automatic1111 is the most popular open source stable diffusion ui and has the biggest open source plug-in ecosystem currently. Nvidia’s compute driver is separate from normal driver and called cuda. Amd’s compute driver is called rocm. Most windows programs like games use apis like directx, Vulkan,metal, web gpu and not cuda. Most ml code was originally intended to run in on scientific computing systems that were Linux. Today the traditional windows gpu apis are tying to get better at gpu ml supports. Amd has no official windows ml code support and is Hoping that other developers figure it out for them but amd made their ml driver open source but no support for consumer graphics cards. Nvidia is proprietary ml driver but guaranteed support across all cards including consumer
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Amd Gpu not utilised
I got it working using SHARK with an AMD RX 480 on Windows 10.
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New to SD - Slow working
Here the link for shark, faster (uses vulkan) than automatic1111 with directml but has less functions https://github.com/nod-ai/SHARK
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7900 XTX Stable Diffusion Shark Nod Ai performance on Windows 10. Seem to have gotten a bump with the latest prerelease drivers 23.10.01.41
I would recommend trying out Nod AI's Shark (That is the link for the most recent 786.exe release), and see how it works for you. From others I've read, it does 512x512 pics at around 3 it/s, which I know isn't mind blowing, but it's good enough to do a pic in about 30 seconds.
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New here
Problem solve, i had it to work i simply put this nod's ai shark exe in my stabble diffusion folder and launch it instead of Webui-user -> Release nod.ai SHARK 20230623.786 · nod-ai/SHARK (github.com)
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I built the easiest-to-use desktop application for running Stable Diffusion on your PC - and it's free for all of you
How does it compare with Shark SD (I am not affiliated with it in any way)? (https://github.com/nod-ai/SHARK)
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after changing GPU from RX 470 4gb to RTX 3060 12GB, I decided to make a few cozy houses, and these are a few of them
you should if you want to run SD on your card https://github.com/nod-ai/SHARK
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20 minute load time per image on high end pc?
Forgive me for not reading you whole comment. I suspect you're version of the SD eb UI doesn't recognize the AMD GPU., so you're using the CPU. AMD GPUs only work with a few web UIs. Try Nod.ai's Shark variant
- AMD support for Microsoft® DirectML optimization of Stable Diffusion
What are some alternatives?
CodeFormer - [NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui-colab - stable diffusion webui colab
stable-diffusion-webui-directml - Stable Diffusion web UI
civitai - A repository of models, textual inversions, and more
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
stable-diffusion-webui-arc-directml - A proven usable Stable diffusion webui project on Intel Arc GPU with DirectML
xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.
AMD-Stable-Diffusion-ONNX-FP16 - Example code and documentation on how to get FP16 models running with ONNX on AMD GPUs [Moved to: https://github.com/Amblyopius/Stable-Diffusion-ONNX-FP16]
k-diffusion-directml - Karras et al. (2022) diffusion models for PyTorch
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.