 How To Use  ```python  from huggingface_hub import hf_hub_download import torch import matplotlib.pyplot as plt import numpy as np from torch import nn  class Generator(nn.Module):     def __init__(self):         super(Generator, self).__init__()         self.main = nn.Sequential(             nn.ConvTranspose2d(100, 64 * 8, 4, 1, 0, bias=False),             nn.BatchNorm2d(64 * 8),             nn.ReLU(True),             nn.ConvTranspose2d(64 * 8, 64 * 4, 4, 2, 1, bias=False),             nn.BatchNorm2d(64 * 4),             nn.ReLU(True),             nn.ConvTranspose2d(64 * 4, 64 * 2, 4, 2, 1, bias=False),             nn.BatchNorm2d(64 * 2),             nn.ReLU(True),             nn.ConvTranspose2d(64 * 2, 64, 4, 2, 1, bias=False),             nn.BatchNorm2d(64),             nn.ReLU(True),             nn.ConvTranspose2d(64, 3, 4, 2, 1, bias=False),             nn.Tanh()         )      def forward(self, input):         return self.main(input)  path = hf_hub_download('huggan/ArtGAN', 'ArtGAN.pt') model = torch.load(path, map_location=torch.device('cpu')) device = 'cuda' if torch.cuda.is_available() else 'cpu'  def generate(seed):     with torch.no_grad():         noise = torch.randn(seed, 100, 1, 1, device=device)     with torch.no_grad():         art = model(noise).detach().cpu()     gen = np.transpose(art[-1], (1, 2, 0))     fig = plt.figure(figsize=(5, 5))     plt.imshow(gen)     plt.axis('off')  generate(25)  ```  