VAE
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3 items • Updated
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("AiArtLab/wan16x_vae", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]=== eval ===
Wan2.2-TI2V-5B | MSE=7.782e-04 PSNR=34.25 LPIPS=0.052 Edge=0.121 KL=9.472 | Z[min/mean/max/std]=[-4.789, -0.012, 4.266, 0.375] | Skew[min/mean/max]=[-0.397, 0.022, 0.653] | Kurt[min/mean/max]=[-0.482, 0.006, 0.538]
AiArtLab/wan16x_vae | MSE=7.275e-04 PSNR=34.51 LPIPS=0.051 Edge=0.118 KL=9.472 | Z[min/mean/max/std]=[-4.789, -0.012, 4.266, 0.375] | Skew[min/mean/max]=[-0.397, 0.022, 0.653] | Kurt[min/mean/max]=[-0.482, 0.006, 0.538]
Wan2.2-T2V-A14B | MSE=7.073e-04 PSNR=34.59 LPIPS=0.048 Edge=0.115 KL=7.781 | Z[min/mean/max/std]=[-15.336, -0.159, 17.703, 2.563] | Skew[min/mean/max]=[-0.343, 0.006, 0.367] | Kurt[min/mean/max]=[-0.538, -0.071, 0.594]
=== percent ===
| Model | MSE | PSNR | LPIPS | Edge | Skew|0 | Kurt|0 |
|----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|
| Wan2.2-TI2V-5B | 100% | 100% | 100% | 100% | 100% | 100% |
| AiArtLab/wan16x_vae | 107.0% | 100.8% | 102.3% | 102.0% | 100.0% | 100.0% |
| Wan2.2-T2V-A14B | 110.0% | 101.0% | 108.0% | 105.1% | 110.1% | 62.1% |
Base repo (eval/train scripts) https://huggingface.co/AiArtLab/simplevae
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