stable-diffusion
stable-diffusion
stable-diffusion | stable-diffusion | |
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20 | 186 | |
338 | 3,145 | |
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0.0 | 0.0 | |
over 1 year ago | 8 months ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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stable-diffusion
- [Machine Learning] [P] Exécutez une diffusion stable sur le GPU de votre M1 Mac
- High-performance image generation using Stable Diffusion in KerasCV
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Charl-e: “Stable Diffusion on your Mac in 1 click”
SD on an Intel mac with Vega graphics runs pretty well though — I think it ran at something like ~3-5 iterations/s for me, which is decent. I ran either https://github.com/magnusviri/stable-diffusion or https://github.com/lstein/stable-diffusion which have MPS support
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Stable Diffusion PR optimizes VRAM, generate 576x1280 images with 6 GB VRAM
https://github.com/magnusviri/stable-diffusion/commit/d0b168...
Copying this change fixed seeds on M1 for me.
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Intel Mac User, How do I start?
You should be able to run it on a CPU. Maybe try this version. If MPS is supported on your Mac you can check this out.
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[P] Run Stable Diffusion on your M1 Mac’s GPU
A group of open source hackers forked Stable Diffusion on GitHub and optimized the model to run on Apple's M1 chip, enabling images to be generated in ~ 15 seconds (512x512 pixels, 50 diffusion steps).
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Run Stable Diffusion on Your M1 Mac’s GPU
Magnusviro [0], the original author of the SD M1 repo credited in this article, has merged his fork into the Lstein Stable Diffusion repo [1], and you can now run Lstein fork with M1 as of a few hours ago.
This adds a ton of functionality - GUI, Upscaling & Facial improvements, weighted subprompts etc.
This has been a big undertaking over the last few days, and I highly recommend checking it out.
[0] https://github.com/magnusviri/stable-diffusion
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How are Mac people using Windows for A.I. stuff?
You can run it on an M1. Using a macbook M1 pro max with 32Gb I get 512x512 in about 50 seconds. use this branch https://github.com/magnusviri/stable-diffusion/tree/apple-mps-support
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ResolvePackageNotFound
I had this error too, and I tried a ton of things to get cudatoolkit to install, without any luck. This fork has an environment-mac.yml file that actually got it working on my M1 Max: https://github.com/magnusviri/stable-diffusion/tree/apple-silicon-mps-support
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If I set a seed value and re-run using the exact same settings, should I get the same image back each time?
But when I run it (locally, using the Mac M1 port), every time I run it creates a different image.
stable-diffusion
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Possible to load Civitai models in basujindal optimizedSD fork?
I am using this repo: https://github.com/basujindal/stable-diffusion and it works fine with e.g. this model: https://huggingface.co/CompVis/stable-diffusion-v-1-4-original
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40min to render 2x 256x256 pictures ..
That includes this optimized version : https://github.com/basujindal/stable-diffusion
- [Stable Diffusion] Coincé chez Unet: courir en mode EPS-Prédiction
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How to use safetensors locally (optimized-sd)?
Ah, I wasn't aware of that. I use this version, which was very easy to set up and use by CLI.
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[Stable Diffusion] stabile Diffusion 1.4 - CUDA-Speicherfehler
Used repo recommended in https://github.com/CompVis/stable-diffusion/issues/39 to use https://github.com/basujindal/stable-diffusion - same result.
- [Stable Diffusion] Aide avec Cuda hors de mémoire
- [Stable Diffusion] Comment créer notre propre modèle?
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Help installing optimisedSD please. Thank you so much!
As per the best solution I found, I have download this (https://github.com/basujindal/stable-diffusion) version and pasted the optimizedSD folder in the main (user>stable-diffusion-webui) folder as per site instruction.
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Stable Diffusion Web UI: Using Optimized SD Post-Installation
The git says you can simply grab the OptimizedSD folder and paste it into the installation path, which I did. However, I'm not sure how to call upon its functionality. Again, the reddit post says >Remember to call the optimized python script python optimizedSD/optimized_txt2img.py instead of standard scripts/txt2img. Though I'm not even sure where that script call is performed. Any ideas? Thanks in advance!
- [Stablediffusion] diffusion stable 1.4 - Erreur CUDA de mémoire insuffisante
What are some alternatives?
openvino - OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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-webui-docker - Easy Docker setup for Stable Diffusion with user-friendly UI
stable-diffusion
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]
diffusers-uncensored - Uncensored fork of diffusers
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
chaiNNer - A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.
rocm-build - build scripts for ROCm
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
stable-diffusion-webui - Stable Diffusion web UI