sd-extension-system-info
SHARK
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sd-extension-system-info | SHARK | |
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51 | 84 | |
252 | 1,354 | |
- | 4.4% | |
9.3 | 9.6 | |
about 2 months ago | 7 days ago | |
Python | Python | |
MIT License | 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.
sd-extension-system-info
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Stable Diffusion in pure C/C++
That seems a lot worse than a 2060 SUPER with PyTorch in A1111.
https://vladmandic.github.io/sd-extension-system-info/pages/... (search for 2060 SUPER)
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Iterations per second benchmarking question
But usually A1111 users use benchmark on this extension https://github.com/vladmandic/sd-extension-system-info
Result can be viewed here https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html
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Best AMD SD Guide for 2023?
AMD SD = Setup Diaster? it was quite troublesome googling the few linux/amdgpu/rocm/sd vers/configs/params posts online. Also the whole PC may hang during generation which is bad for the harddisk. Your card is way more powerful so may not hang like mine. People are getting 8it/s https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html
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--medvram. Should I remove this flag? Running 3090
Anyway to properly "benchmark" the impacts different switches on your image generation speed, it is better to use the benchmarking utility from extension https://github.com/vladmandic/sd-extension-system-info (it also creates a very handy table of results from other users at https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html for you to compare with.
- See the performance of a 4090 in action.
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What GPU everyone running?
i'm using a RTX 2060 6GB, i can run a batch of 12 * [512*768] without problems. For GPU i like the RTX 3060 12GB, RTX 4060Ti 16GB, 3090 24GB or well a RTX 4090 24GB, you can check some benchmarks here
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Tips on improving it/s on rtx 3080? Is 3-4it/s normal for this card?
your it/s are low, it/s depends on other things, like sampler, resolution, batch size... here is a list, you can install the extension and do a benchmark too.
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Self-reported GPUs and iterations/second based on the "vladmatic" data as of today
It's done using https://github.com/vladmandic/sd-extension-system-info
That's where the vlad stats can be useful, find your card, sort by it/sec, and see what they're doing/running and if you're doing the same. https://vladmandic.github.io/sd-extension-system-info/pages/benchmark.html
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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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'm using Nod AI's Shark Distributables which you can get from their GitHub. Getting it all going was quite a fun learning experience. Don't ask me how to install it, but there are plenty of "how to videos", which is how I got it figured out.
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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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
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SD just released an open source version of their GUI called StableStudio
I run an open source 2D graphics editor project and our license is Apache 2.0 (which is basically the same as MIT) which provides much more freedom than the GPL does, since it's not copyleft. We have a Stable Diffusion feature built in, and we want to provide a hosted component so users can utilize that feature without self-hosting. A1111 being AGPL likely means we have to find an alternate backend. I'm looking into other options like SHARK (and would love some ideas if anyone else has suggestions).
What are some alternatives?
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui-directml - Stable Diffusion web UI
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
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]
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
llama.cpp - LLM inference in C/C++
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
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]
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
civitai - A repository of models, textual inversions, and more