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license: mit |
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A collection of regularization / class instance datasets for the [Stable Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) model to use for DreamBooth prior preservation loss training. Files labeled with "mse vae" used the [stabilityai/sd-vae-ft-mse](https://huggingface.co/stabilityai/sd-vae-ft-mse) VAE. For ease of use, datasets are stored as zip files containing 512x512 PNG images. The number of images in each zip file is specified at the end of the filename. |
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Currently this repository contains the following datasets (datasets are named after the prompt they used): |
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* "**artwork style**": 4125 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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* "**illustration style**": 3050 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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* "**fighter jet**": 1600 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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* "**train**": 2669 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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* "**person**": 2115 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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* "**woman**": 4420 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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* "**erotic photography**": 2760 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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* "**supermodel**": 4411 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE. |
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I used the "Generate Forever" feature in [AUTOMATIC1111's WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) to create thousands of images for each dataset. Every image in a particular dataset uses the exact same settings, with only the seed value being different. |
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You can use my regularization / class image datasets with: https://github.com/ShivamShrirao/diffusers, https://github.com/JoePenna/Dreambooth-Stable-Diffusion, https://github.com/TheLastBen/fast-stable-diffusion, and any other DreamBooth projects that have support for prior preservation loss. |
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