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 Stable Diffusion 1.5 fine tuned VAE decoder for better pixel art generation by aliasing the output of the decoder.
 Fine tuning was done by training 50 thousand images for 1 epoch effective batch size 12. I preprocessed the images to quantize each 8x8 tile to its average color. On a RTX3090, this took about 4 hours to fine-tune. Used only MSE loss at 1e-5 learning rate. The training data set was just generated from other stable diffusion models, mostly cartoon-like images.

 Stable Diffusion 1.5 fine tuned VAE decoder for better pixel art generation by aliasing the output of the decoder.
+![comparison](https://huggingface.co/thomaseding/vae-teding-aliased-2024-03/resolve/main/comparison.png)
 Fine tuning was done by training 50 thousand images for 1 epoch effective batch size 12. I preprocessed the images to quantize each 8x8 tile to its average color. On a RTX3090, this took about 4 hours to fine-tune. Used only MSE loss at 1e-5 learning rate. The training data set was just generated from other stable diffusion models, mostly cartoon-like images.

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