stable-diffusion-ui
Dreambooth-Stable-Diffusion
stable-diffusion-ui | Dreambooth-Stable-Diffusion | |
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249 | 100 | |
6,808 | 3,166 | |
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9.9 | 6.8 | |
11 months ago | 4 months ago | |
JavaScript | Jupyter Notebook | |
GNU General Public License v3.0 or later | MIT License |
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stable-diffusion-ui
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Useful Links
CMDR2's 1-Click Installer
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Best current stable diffusion UI app?
Hey so i'm currently using easydiffusion but its missing one feature i've been really wanting to play around with recently. Video, and i've heard from some others that its one of the easiest to install but least peformant and worse options you can get; so what do you guys suggest?
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The softer side of self hosting: The aesthetics, logos
Or just use the CPU and it works, just takes a few minutes. stable diffusion cpu But don't let me stop you, I need one too.
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So how is nvidia gpu experience these days?
No. CUDA is very straightforward. There is even a nice project that sets up Stable Diffusion for you. With basically no knowledge about AI i was able to get it to run. If i recall correctly i just needed to install one dependency manually, and i was provided with nice web gui for playing with it.
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Models and samplers…
You could read the guide first: https://github.com/cmdr2/stable-diffusion-ui/wiki/UI-Overview or Start easy diffusion
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Could someone please make my wife into a realistic sculpture/statue? Will tip $50 for a perfect one!
Thanks and your right there are loads, trying out this from GitHub
- What is the text-to-image AI tool?
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Tip for a (kinda) newbie
Simplest start https://github.com/cmdr2/stable-diffusion-ui
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SD privacy? Offline? Concerns?
First is Easy Diffusion, you need to be online just once to run the installer. It downloads several extra files. Let it finish and then make some test pictures. Exit everything (browser window and text window). Then anytime you want to run it, just turn off internet and run the batch file to start it up. No internet!
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Need help installing SD on AMD!!
Yesterday I got Easy Diffusion to work (on Windows only), but it refuses to use the GPU and instead uses the CPU, which of course, takes nearly an hour to make a 512x512 image.
Dreambooth-Stable-Diffusion
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Will there be comprehensive tutorials for fine-tuning SD XL when it comes out?
Tons of stuff here, no? https://github.com/JoePenna/Dreambooth-Stable-Diffusion/
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Useful Links
Joe Penna's Dreambooth (Tutorial|24GB) Most popular DB repo with great results.
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Dreambooth / Custom Training / Model - what's the state of the art?
1) The https://github.com/JoePenna/Dreambooth-Stable-Diffusion instructions say to use the 1.5 checkpoints - is that the latest? Can I use the 2+ models or?
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My Experience with Training Real-Person Models: A Summary
I quickly turned to the second library, https://github.com/JoePenna/Dreambooth-Stable-Diffusion, because its readme was very encouraging, and its results were the best. Unfortunately, to use it on Colab, you need to sign up for Colab Pro to use advanced GPUs (at least 24GB of VRAM), and training a model requires at least 14 compute units. As a poor Chinese person, I could only buy Colab Pro from a proxy. The results from JoePenna/Dreambooth-Stable-Diffusion were fantastic, and the preparation was straightforward, requiring only <=20 512*512 photos without writing captions. I used it to create many beautiful photos.
- I Used Stable Diffusion and Dreambooth to Create an Art Portrait of My Dog
- training
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Training a model on Iwanaga Kotoko (from in/spectre), which step do you guys think the model is at its best?
I've found EveryDream to be brilliant and have switched from JoePenna's Dreambooth because I've found I get better results so long as I provide good captions for all the images, even if preparing the dataset takes 3x as long (took me 2 hours to crop and label the 54 images).
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Dreambooth training results for face, object and style datasets with various prior regularization settings.
From what I know you can train with whatever size you want. But you need software that will support it. For example, ShivamShrirao/diffusers repo seems to allow a change of dimension. Also, you need HW that would support the training, because bigger images need more VRAM, for example,Joe Penna repo is using ~23GB with 512x512px so probably it's not a valid option. But the ShivamShrirao repo has optimizations that allow to run it with less VRAM.
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Starting to get quite good results with Dreambooth. What do you think? (Follow @RokStrnisa on Twitter for more.)
This is a good starting place: https://github.com/JoePenna/Dreambooth-Stable-Diffusion
- I'm a N00b with training stuff. Trying to get runpod with Dreambooth training some images (80 total) and I'm getting this error. Help?
What are some alternatives?
stable-diffusion-webui - Stable Diffusion web UI
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
Stable-Diffusion-Regularization-Images - For use with fine-tuning, especially the current implementation of "Dreambooth".
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
A1111-Web-UI-Installer - Complete installer for Automatic1111's infamous Stable Diffusion WebUI
civitai - A repository of models, textual inversions, and more
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
SHARK - SHARK - High Performance Machine Learning Distribution
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.