Dreambooth-Stable-Diffusion
sd-enable-textual-inversion
Dreambooth-Stable-Diffusion | sd-enable-textual-inversion | |
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47 | 26 | |
7,383 | 744 | |
- | - | |
0.0 | 6.5 | |
over 1 year ago | over 1 year ago | |
Jupyter Notebook | Python | |
MIT License | - |
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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
sd-enable-textual-inversion
- Stable Diffusion links from around September 11, 2022 that I collected for further processing
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aiART genertion from an image database.
Yes, what you’re describing can be done using textual inversion.
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Did GoogleAI Just Snooker One of Silicon Valley’s Sharpest Minds?
https://github.com/hlky/sd-enable-textual-inversion
It creates a representation of an entity and allows rending it in different styles and contexts. Currently it involves model fine tuning, but I expect it will become convenient as the power of the operation becomes clear. And once it's convenient, you'll be able to do the progressive queries you're asking for (and it'll be a lot easier to create narratively coherent sets of images.)
- My findings using Textual Inversion for Stable Diffusion
- Question: Does anyone know if it is possible to generate the same image but in different views (like left view, top view, close-up etc) ?
- Could someone make a GUI Textual inversion guide for noobs?
- Useful link
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Teach new concepts to Stable Diffusion with 3-5 images only - and browse a library of learned concepts to use
A branch to add it to SD (which I think the original now has): https://github.com/hlky/sd-enable-textual-inversion
- Further training of stable diffusion
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I don't know anything about python or programming. How can I easily create a .pt file for use with embedding, to generate content based on trained image?
Hey now, there's still an option out there, this Colab notebook, it's able to run on the free tier of Colab. By default, it runs for about 2 hours per embed, and the files made can be used both in the notebook, and on Hlky's front-end, after enabling it, and setting to full precision.
What are some alternatives?
xformers - Hackable and optimized Transformers building blocks, supporting a composable construction.
textual_inversion
stable-diffusion-webui - Stable Diffusion web UI
SHARK - SHARK - High Performance Machine Learning Distribution
Stable-textual-inversion_win
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
stable-diffusion
StableTuner - Finetuning SD in style.
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]
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]