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README.md

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----
-license: wtfpl
----
+---
+                        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(
+  (encoder): Sequential(
+    (0): Conv2d(3, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (1): ReLU(inplace=True)
+    (2): Conv2d(64, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (3): ReLU(inplace=True)
+    (4): Conv2d(128, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (5): ReLU(inplace=True)
+  )
+  (decoder): Sequential(
+    (0): ConvTranspose2d(256, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (1): ReLU(inplace=True)
+    (2): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (3): ReLU(inplace=True)
+    (4): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1))
+    (5): Tanh()
+  )
+)
+