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README.md

@@ -1,31 +1,34 @@
 ---
-                        tags:
-                        - unet
-                        - pix2pix
-                        library_name: pytorch
-                        ---
-                        
-                        # Pix2Pix UNet Model
-                        
-                        ## Model Description
-                        Custom UNet model for Pix2Pix image translation.
-                        - Image Size: 256
-                        - Model Type: Small (256)
-                        
-                        ## Usage
-                        
-                        ```python
-                        import torch
-                        from small_256_model import UNet as small_UNet
-                        from big_1024_model import UNet as big_UNet
-                        
-                        # Load the model
-                        checkpoint = torch.load('model_weights.pth')
-                        model = big_UNet() if checkpoint['model_config']['big'] else small_UNet()
-                        model.load_state_dict(checkpoint['model_state_dict'])
-                        model.eval()
-                        Model Architecture
-                        UNet(
+tags:
+- unet
+- pix2pix
+- pytorch
+library_name: pytorch
+---
+
+# Pix2Pix UNet Model
+
+## Model Description
+Custom UNet model for Pix2Pix image translation.
+- **Image Size:** 256
+- **Model Type:** Small (256)
+
+## Usage
+
+```python
+import torch
+from small_256_model import UNet as small_UNet
+from big_1024_model import UNet as big_UNet
+
+# Load the model
+checkpoint = torch.load('model_weights.pth')
+model = big_UNet() if checkpoint['model_config']['big'] else small_UNet()
+model.load_state_dict(checkpoint['model_state_dict'])
+model.eval()
+
+Model Architecture
+
+UNet(
   (encoder): Sequential(
     (0): Conv2d(3, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
     (1): ReLU(inplace=True)
@@ -42,5 +45,4 @@
     (4): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
     (5): Tanh()
   )
-)
-                    
+)