pix2pix_flux

---

                    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() ) )