import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Heasterian/AsymmetricAutoencoderKLUpscaler_v2", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Another take on upscaler using AsymmetricAutoencoderKL, in this case I did re-use decoder of ostris/vae-kl-f8-d16 as decoder and trained just encoder.
Oversharpening was reduced by usage of sobel in loss calculation. I guess that without high resolution image used as reference, it might look more blury than previous one.
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