MIOpen
SHARK
MIOpen | SHARK | |
---|---|---|
9 | 84 | |
983 | 1,385 | |
1.4% | 1.6% | |
9.7 | 9.4 | |
5 days ago | 4 days ago | |
Assembly | 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.
MIOpen
- AI Libraries and AI Frameworks are "Not Available" for ROCm on Windows. Does that mean not yet, or never?
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[Project] MLC LLM: Universal LLM Deployment with GPU Acceleration
More than three months behind schedule...
- Someone has run SD with a release candidate of ROCm 5.5 on RDNA 3 and gets 15 it/s
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ROCm on a 7900 XTX
https://github.com/ROCmSoftwarePlatform/MIOpen/milestones Miopen for rocm 5.5 and 5.6 milestones are done.But you don't release those yet.I still don't understand, what is the point of selling AI/ML capable GPU without releasing the driver for that (rocm, etc).
- Sapphire Pulse 7900 xt (Techpowerup review)
- Man I wish I could do all this cool shit too
- Issues with Automatic1111 WebUI on Ubuntu 22.04.1 LTS with AMD GPU
- Miopen - AMD's Machine Intelligence Library
- Radeon ROCm 4.3 Released With HMM Allocations, Many Other Improvements
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?
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
stable-diffusion-webui - Stable Diffusion web UI
ROCm - AMD ROCm™ Software - GitHub Home [Moved to: https://github.com/ROCm/ROCm]
stable-diffusion-webui-directml - Stable Diffusion web UI
k-diffusion-directml - Karras et al. (2022) diffusion models for PyTorch
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
stablediffusion-directml - High-Resolution Image Synthesis with Latent Diffusion Models
xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.
SillyTavern - LLM Frontend for Power Users. [Moved to: https://github.com/SillyTavern/SillyTavern]
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.