OnnxDiffusersUI
stable-diffusion-webui
OnnxDiffusersUI | stable-diffusion-webui | |
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26 | 2,808 | |
189 | 130,470 | |
- | - | |
4.9 | 9.9 | |
12 months ago | 5 days ago | |
Python | Python | |
GNU Affero General Public License v3.0 | MIT |
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OnnxDiffusersUI
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AMD GPU
Sounds like Automatic1111 doesn't work with your AMD RX570 so it uses your CPU instead. There's a guy that tried a few workarounds on his github page that might help but you basically need to buy a GPU made in the last 3 years that has ray tracing capability. https://github.com/azuritecoin/OnnxDiffusersUI
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Useful Links
Onnx Diffusers UI
- AMD support for Microsoft® DirectML optimization of Stable Diffusion
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[Help] using custom model
Its this one: https://github.com/azuritecoin/OnnxDiffusersUI It works properly except i can't convert models other than the default it comes with.
- [Stable Diffusion] J'ai créé ma propre interface utilisateur pour exécuter SD sur AMD GPU sur Windows
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Best option for running on an AMD GPU.
https://github.com/azuritecoin/OnnxDiffusersUI this seems to work pretty good for me, has quite a bit of features and has a CPU only mode, only problem with it is, it hogs a lot of ram
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Best UI for AMD Card
for windows the onnx ui:https://github.com/azuritecoin/OnnxDiffusersUI, or you can try and fenagle your way into installing automatic1111 on linux
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How Nvidia’s CUDA Monopoly In Machine Learning Is Breaking - OpenAI Triton And PyTorch 2.0
Guide
- AMD on Windows and RX580 Failed
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AMD GPU, SD and Linux on WSL2, any success story?
I also have a 6800 and when I'm on Windows I mess around with this https://github.com/azuritecoin/OnnxDiffusersUI which is fine and works okay but yeah without ROCm it is very slow. I usually just dualboot into Linux if I want to spend more time generating things. It's just how it is for now with support for AMD, sadly.
stable-diffusion-webui
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Show HN: I made an app to use local AI as daily driver
* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.
- https://diffusionbee.com/
- https://github.com/comfyanonymous/ComfyUI
- https://github.com/AUTOMATIC1111/stable-diffusion-webui
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
I would love to be able to have a native stable diffusion experience, my rx 580 takes 30s to generate a single image. But it does work after following https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...
I got this up and running on my windows machine in short order and I don't even know what stable diffusion is.
But again, it would be nice to have first class support to locally participate in the fun.
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Ask HN: What is the state of the art in AI photo enhancement?
In Auto1111, that just uses Image.blend. :)
https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...
- How To Increase Performance Time on MacOS
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Can anyone suggest an AI model that can help me enhance a poorly drawn logo?
I used SDXL in automatic1111 webui for both images. Now that I think about it, the procedure I described was how I made this one, but the one that looks like an illustration was done in two steps. I used the canny ControlNet as I said for the outer part of the logo to preserve the shape of the fonts, but I had to turn it off for the boot to give SDXL leeway to add detail and make it look more like a boot.
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Seeking out an experienced and empathetic coding buddy.
That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.
- can't get it working with an AMD gpu
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SD extension that allows for setting override
Possibly Unprompted? https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8094
- Need to write an application to use Stable Diffusion on my desktop PC - which resource should I learn to use?
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4090 Speed Decrease on each Generation/Iteration
version: v1.6.1 • python: 3.10.13 • torch: 2.0.1+cu118 • xformers: 0.0.20 • gradio: 3.41.2 • checkpoint: 6e8d4871f8
What are some alternatives?
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.
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]
stable-diffusion-webui - Stable Diffusion web UI
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
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]
SHARK - SHARK - High Performance Machine Learning Distribution
A1111-Web-UI-Installer - Complete installer for Automatic1111's infamous Stable Diffusion WebUI
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
stable-diffusion-webui-directml - Stable Diffusion web UI
IOPaint - Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures.
safetensors - Simple, safe way to store and distribute tensors