Update README.md

README.md

@@ -46,14 +46,5 @@ $$
 | GAN Start Step        | 50,000                     |
 | KL Annealing          | Yes (10% of training)      |
 | Augmentations         | Crop, flip, jitter, blur, rotation |
-Trained using a cosine learning rate schedule with gradient clipping and automatic mixed precision (`torch.cuda.amp`)
-## Usage Example
-```python
-import torch
-from diffusers import AutoencoderKL
-vae = AutoencoderKL.from_pretrained("gabehubner/vae-256px-8z")
-vae.eval()
 
-input_tensor = torch.randn(1, 3, 256, 256)  # Replace with your actual input
-with torch.no_grad():
-    output = vae(input_tensor).sample
+Trained using a cosine learning rate schedule with gradient clipping and automatic mixed precision (`torch.cuda.amp`)