model upload

.gitattributes

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README.md

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 ---
 license: mit
 ---
+
+# VAE for high-resolution image generation with stable diffusion
+
+This VAE is trained by adding only one step of noise to the latent and denoising the latent with U-net, to avoid oversensitivity to latent.
+This process reduces the possibility to describe too much detail in some objects, such as plants and eyes, etc., than in the surroundings when generated at high resolution.
+The dataset consists of 19k images tagged nijijourneyv5 and published on the web, and was denoised using [the same dataset trained models](https://huggingface.co/Ai-tensa/FlexWaifu).
+
+## sample
+
+![](xyz_grid-0011-1798392412.png)
+
+## training details
+
+- 19k 1images
+- 2 epochs
+- Aspect Ratio Bucketing based on 768p resolution
+- multires noise
+- lr: 1e-5
+- precision: fp32

mistVAE.safetensors

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