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Taming Transformers for High-Resolution Image Synthesis

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Hi, thank you for sharing your amazing work. I want to play with it a bit and especially with my own segmentation maps, where I can find which color represents...

are there ways to reduce inference time? Currently takes about 13 minutes on a k80 for the norway example at 432x288

Has this approach been extended to use BERT based transformer instead of GPT?

how to harmonize image?

Dear authors Thank you for your great work. I tried to work on my own task based on your great work. What I need to do is to generate new...

im recieving a syntax error via stable-diffusion, but i cant find the error through vs2019, here is what i saw ![image](https://user-images.githubusercontent.com/103824763/195737560-e2ddc012-9888-45e7-9ade-7a417a6065df.png)

Thanks for your great work. I want to use my own dataset for autoencoder. I use the environment of custom_vqgan.yaml. And I would appreciate it if you could tell me...

I get this error when executing stable diffusion: ![IMG_20220902_010908.jpg](https://user-images.githubusercontent.com/112648460/188082184-203752f3-3f9f-415d-8088-10e46f3d75ef.jpg)