SHARK
stable-diffusion-webui-directml
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SHARK | stable-diffusion-webui-directml | |
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84 | 74 | |
1,382 | 1,551 | |
4.1% | - | |
9.4 | 9.9 | |
3 days ago | 6 days ago | |
Python | Python | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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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
stable-diffusion-webui-directml
- stable diffusion compliant with amd gpu or not?
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RuntimeError: Could not allocate tensor with 4915840 bytes. There is not enough GPU video memory available!
I'm getting this error using (https://github.com/lshqqytiger/stable-diffusion-webui-directml/issues), freshly installed. I'm running it on an AMD RX 6700 XT with 12gb of vram. Generating a single image at default settings (512x512, 20 steps, etc.) I can do simple prompts (i.e. "kitty cat") but as soon as I add a couple more tags, I get the aforementioned error message, usually 20-30% into generating an image. I went through this thread (https://github.com/lshqqytiger/stable-diffusion-webui-directml/issues/38) and tried every solution I saw, most of them being variations of adding --medvram --precision full --no-half --no-half-vae --opt-split-attention-v1 --opt-sub-quad-attention --disable-nan-check to the commandline arguments. What else might I be able to try? Thanks.
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Best AMD SD Guide for 2023?
i use automatic 1111 you can find the installation on the github , this branch https://github.com/lshqqytiger/stable-diffusion-webui-directml and it works fine although the speed is what it is, i also have a old GPU.
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Just how much VRAM do I need? It keeps saying I don't have enough with a 7900xt.
I'm using this one: https://github.com/lshqqytiger/stable-diffusion-webui-directml
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I am confused regarding same seed = same picture. Any explanations or insights? The journey for this in comments.
- https://github.com/lshqqytiger/stable-diffusion-webui-directm - starting webuser-ui with COMMANDLINE_ARGS=--opt-sub-quad-attention –disable-nan-check - AMD 8GB Radeon Pro WX7100
- ¿Quién fue a la marcha contra la IA en el Obelisco? Cuenten cómo estuvo
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StableDiffusion will only use my CPU?
I'm running this fork (https://github.com/lshqqytiger/stable-diffusion-webui-directml) on a pc with a Ryzen 5700x and a Radeon RX 6700 XT 12 GB Video Card.
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(AMD) Random Running Out of Memory Error After Generation
I am using direct-ml fork
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Stable Diffusion on AMD 6900XT is Super Slow
Im running Stable diffusion on my 6900XT, and I feel like its way slower than normal. Using the updated Webui https://github.com/lshqqytiger/stable-diffusion-webui-directml.
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Stable Diffusion DirectML on AMD APU only (no external GPU) - Ram Usage?
This refers to the use of iGPUs (example: Ryzen 5 5600G). No graphic card, only an APU. The DirectML Fork of Stable Diffusion (SD in short from now on) works pretty good with AMD. But not only with the GPUs, but also with only-APUs without GPUs.
What are some alternatives?
stable-diffusion-webui - Stable Diffusion web UI
StableDiffusionUI - Stable Diffusion UI: Diffusers (CUDA/ONNX)
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
sd-webui-controlnet - WebUI extension for ControlNet
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.
OnnxDiffusersUI - UI for ONNX based diffusers
llama.cpp - LLM inference in C/C++
multidiffusion-upscaler-for-automatic1111 - Tiled Diffusion and VAE optimize, licensed under CC BY-NC-SA 4.0