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Better sorting of datasets in description

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  1. README.md +14 -4
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@@ -7,13 +7,15 @@ A collection of regularization / class instance datasets for the [Stable Diffusi
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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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@@ -21,12 +23,20 @@ Currently this repository contains the following datasets (datasets are named af
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  * "**guy**": 4820 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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-
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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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  * "**kitty**": 5100 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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  Currently this repository contains the following datasets (datasets are named after the prompt they used):
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+ Art Styles
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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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+ * "**erotic photography**": 2760 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE.
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+ People
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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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  * "**guy**": 4820 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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+ * "**bikini model**": 4260 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE.
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+ Animals
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+
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  * "**kitty**": 5100 images generated using 50 DDIM steps and a CFG of 7, using the MSE VAE.
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+ Vehicles
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+
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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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+
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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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+
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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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