Dreambooth-Stable-Diffusion
stable-diffusion
Dreambooth-Stable-Diffusion | stable-diffusion | |
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47 | 142 | |
7,383 | 2,438 | |
- | - | |
0.0 | 9.8 | |
over 1 year ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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Dreambooth-Stable-Diffusion
- Where can I train my own LoRA?
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I am having an error with ControlNet (RuntimeError: CUDA error: CUBLAS_STATUS_ALLOC_FAILED when calling `cublasCreate(handle)`)
I did search online for an answer, but I am a PC noob, I didn't know what to do when I found this solution in this link: https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/issues/113
- True to life photorealism v2
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How can to create a custom image generation model?
Do you know some projects or guided tutorials that could help me? How many drawings with the desired style I should then have to give to train the AI model? I found Dreambooth on Stable Diffusion but it seams to be for another use case.
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How to Make Your Own Anime (Linux/Mac Tutorial follow along)
This seems to be an issue with the code and or the environment itself. There is an open bug for this where some suggestions are p provided by others on how to fix. https://github.com/XavierXiao/Dreambooth-Stable-Diffusion/issues/47
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AI generated portraits of Myself as different classes: Looking for opinion!
Could you provide some more detail on how this works? Did you just use this GitHub repository or did you put together your own implementation?
- Looking for an AI model to transform a video of me (full body) into an animated avatar. Does something like this exist?
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Ray Liotta as Tommy Vercetti from GTA Vice City
I think the best way to do this would be to train Dreambooth on a number of photos of Ray Liotta first, and use Stable Diffusion instead. https://github.com/XavierXiao/Dreambooth-Stable-Diffusion
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Luddites don't have a issue with AI, just that it "steals" from them (it doesn't). But they also have a issue with using your own child's drawings as a reference.
Dreambooth. There are other ways, but that is the gold standard. It takes even more Vram than regular stable diffusion, so if you don't have a very beefy card (e.g. 4090 with 25 GB VRAM) various websites let you do it onlin for a small fee. You then download a new model that has all the old stuff (e.g.the 4 gigabyte SD 1.5 file) plus your new images. Like I said, there are other ways that are easier, but when people show great results they are usually talking about Dreambooth.
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Bunch of misinformation being spread in this thread
THE CODE (unofficial implementation, for the exact wording stating how little images you need read the paper) is designed with extremely little data in mind. I don't know how else to phrase it dude, do you think the training is a magic black box that runs with snail neurons? If you train a dreambooth model the jupyter ide makes calls to python files, those are the files. That is the code
stable-diffusion
- [Stable Diffusion] Aide nécessaire à l'augmentation de la taille du fichier maximum sur l'installation locale
- [Machine Learning] [P] Exécutez une diffusion stable sur le GPU de votre M1 Mac
- Its time!
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Anybody running SD on a Macbook Pro? What are you using and how did you install it?
Yes, you can install it with Python! https://github.com/lstein/stable-diffusion works with macOS, and you can control all the common parameter via their WebUI or CLI :)
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How do I save the arguments for images I create when using the terminal? (Apple M1 Pro)
I'm using lstein fork ("dream") and when I create an image from the terminal, it also writes back to the terminal like this:
- I Resurrected “Ugly Sonic” with Stable Diffusion Textual Inversion
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AI Seamless Texture Generator Built-In to Blender
> Whenever I ask for something like ‘seamless tiling xxxxxx’ it kinda sorta gets the idea, but the resulting texture doesn’t quite tile right.
Getting seamless tiling requires more than just have "seamless tiling" in the prompt. It also depends on if the fork you're using has that feature at all.
https://github.com/lstein/stable-diffusion has the feature, but you need to pass it outside the prompt. So if you use the `dream.py` prompt cli, you can pass it `"Hats on the ground" --seamless` and it should be perfectly tilable.
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Auto SD Workflow - Update 0.2.0 - "Collections", Password Protection, Brand new UI + more
From https://github.com/lstein/stable-diffusion
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Stable Diffusion GUIs for Apple Silicon
Stable Diffusion Dream Script: This is the original site/script for supporting macOS. I found this soon after Stable Diffusion was publicly released and it was the site which inspired me to try out using Stable Diffusion on a mac. They have a web-based UI (as well as command-line scripts) and a lot of documentation on how to get things working.
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Still can't believe this technology is real. My talentless 2 minute sketch on the left.
I’m pretty sure it works for M2 as well - basically the newer ARM-based Macs. The instructions to get it working are detailed! https://github.com/lstein/stable-diffusion
What are some alternatives?
xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.
waifu-diffusion - stable diffusion finetuned on weeb stuff
stable-diffusion-webui - Stable Diffusion web UI
taming-transformers - Taming Transformers for High-Resolution Image Synthesis
SHARK - SHARK - High Performance Machine Learning Distribution
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
diffusers-uncensored - Uncensored fork of diffusers
StableTuner - Finetuning SD in style.
txt2imghd - A port of GOBIG for Stable Diffusion
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
dream-textures - Stable Diffusion built-in to Blender