stable-diffusion-webui-directml
unpaint
stable-diffusion-webui-directml | unpaint | |
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74 | 6 | |
1,577 | 258 | |
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9.9 | 8.2 | |
7 days ago | about 1 month ago | |
Python | C++ | |
GNU Affero General Public License v3.0 | GNU General Public License v3.0 or later |
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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.
unpaint
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I ported Stable Diffusion onto Xbox Series X and S.
Here are the details: Running Unpaint on the Xbox Series consoles · axodox/unpaint Wiki (github.com)
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Unpaint: a compact, fully C++ implementation of Stable Diffusion with no dependency on python
I also started to build an app of my own on top of it called Unpaint (which you can download and try following the link), targeting Windows and (for now) DirectML. The app provides the basic Stable Diffusion pipelines - it can do txt2img, img2img and inpainting, it also implements some advanced prompting features (attention, scheduling) and the safety checker. It is lightweight and starts up quickly, and it is just ~2.5GB with a model, so you can easily put it on your fastest drive. Performance wise with single images is on par for me with CUDA and Automatic1111 with a 3080 Ti, but it seems to use more VRAM at higher batch counts, however this is a good start in my opinion. It also has an integrated model manager powered by Hugging Face - though for now I restricted it to avoid vandalism, however you can still convert existing models and install them offline (I will make a guide soon). And as you can see on the above images: it also has a simple but nice user interface.
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Looking for a "censored" or "SFW" 1.5 model
The source code is on GitHub (here: axodox/native-diffusion (github.com)), there is also an installer in releases, if you want to try it.
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Nvidia: "2x performance improvement for Stable Diffusion coming in tomorrow's Game Ready Driver"
I made a C++ test project here: Release Olive Test · axodox/native-diffusion (github.com)
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Stable Diffusion XUI for Nvidia and AMD GPU
Well, I am working on a port of StableDiffusion which uses C++ only, no python, no other dependencies and crap. I have txt2img, img2img and inpainting fully working now.
What are some alternatives?
SHARK - SHARK - High Performance Machine Learning Distribution
Olive - Olive is an easy-to-use hardware-aware model optimization tool that composes industry-leading techniques across model compression, optimization, and compilation.
StableDiffusionUI - Stable Diffusion UI: Diffusers (CUDA/ONNX)
a1111-sd-webui-locon - A extension for loading LyCORIS model in sd-webui
sd-webui-controlnet - WebUI extension for ControlNet
automatic - SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models
axodox-machinelearning - This repository contains a pure C++ ONNX implementation of multiple offline AI models, such as StableDiffusion (1.5 and XL), ControlNet, Midas, HED and OpenPose.
stable-diffusion-webui - Stable Diffusion web UI
azurelinux - Linux OS for Azure 1P services and edge appliances
OnnxDiffusersUI - UI for ONNX based diffusers
SDAtom-WebUi-us - Queue system for AUTOMATIC1111's webui