VAEs
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import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Anzhc/Z-Image_Anime_VAE", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Z-Image Anime VAE
Introduction
A Decoder finetune(That means it can be used as-is) of the Z-Image (Flux) AE on a dedicated anime illustration dataset.
It allows to reduce high frequency compression artifacts and oversharpening, that are inherent to realism data.
Additionally helps with higher resolution, when multiple re-encodes are involved.
As of now, it is not extremely useful, as we don't have anime base yet, but i've seen quite a few anime gens done, so why not. And Tongyi team plans to do something with anime data, so im patiently waiting.
Visual Examples
1-2-4k hires:
1-2k hires:
Full comparison: https://slow.pics/c/kmCwRG4l
Usage
Load as VAE instead of ae.safetensors
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Model tree for Anzhc/Z-Image_Anime_VAE
Base model
Tongyi-MAI/Z-Image-Turbo