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Dreambooth-SD-optimized reviews and mentions
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Rtx 4070 Ti which dreambooth could fit
Hey guys im quite new to dream booth i tried the one in stabel diffusion but wasnt really satisfied with the output. Im lloking for a external dreambooth that could be started with anaconda but doesnt need 24 gb Vram i only have 12 Gb. I tried gammagec / Dreambooth-SD-optimizedbut he says you need at least 24 GB
- Best Local SD/Dream Both Combination For Those With 24GB Cards
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Update 1.7.0 of my Windows SD GUI is out! Supports VAE selection, prompt wildcards, even easier DreamBooth training, and tons of quality-of-life improvements. Details in comments.
Using this GitHub https://github.com/gammagec/Dreambooth-SD-optimized from this guide https://pastebin.com/xcFpp9Mr
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Questions about training parameters.
I had pretty good results with 20 images of myself, 200 reg images and 6000 step using https://github.com/gammagec/Dreambooth-SD-optimized.
- [Dreambooth] I changed something about the way Dreambooth training works. Tell me what you think, please.
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First full music video with Deforum 0.5 (single render)
I use Automatic1111 for SD and then Dreambooth Optimized https://github.com/gammagec/Dreambooth-SD-optimized to do custom models.
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How to increase the value of the num_workers?
Gammagec Dreambooth-SD-optimized - https://github.com/gammagec/Dreambooth-SD-optimized
- [Guide] DreamBooth Training with ShivamShrirao's Repo on Windows Locally
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Looking to replicate these kind of effects in stable diffusion. Anyone know what prompts/techniques would be involved? I'd guess they used img2img + ebsynth?
I use this dreambooth repo to train the SD model. https://github.com/gammagec/Dreambooth-SD-optimized Here's the video that shows how to install it in very good detail. https://youtu.be/TwhqmkzdH3s He uses it to train in a face but you can use it to train in a style as well. I suggest taking about 15 or 20 detailed frames of the video and training it in as a style for the class name. You'll have to experiment with how many training steps to take. I suggest doing 1,000 steps at a time and testing out the model. Also don't leave the default "sks", the researchers forgot that that's a common acronym if you know what I mean. Do something like my_style1 so the model doesn't get confused with something else.
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Fewer steps produce more clear images
I'm using this guide: https://www.reddit.com/r/StableDiffusion/comments/xpoexy/yet_another_dreambooth_post_how_to_train_an_image/ to train locally with this repo https://github.com/gammagec/Dreambooth-SD-optimized on windows. Needs a 24gb card though.
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gammagec/Dreambooth-SD-optimized is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of Dreambooth-SD-optimized is Jupyter Notebook.
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