content: import torch
  import torchvision.models as models
  
  # Example of saving a model
  model = models.resnet18(pretrained=True)
  torch.save(model.state_dict(), 'model_weights.pth')
  
  # Example of loading the model weights in an insecure way (should trigger B614)
  loaded_model = models.resnet18()
  loaded_model.load_state_dict(torch.load('model_weights.pth'))
  
  # Example of loading with weights_only=True (should NOT trigger B614)
  safe_model = models.resnet18()
  safe_model.load_state_dict(torch.load('model_weights.pth', weights_only=True))
  
  # Example of loading with weights_only=False (should trigger B614)
  unsafe_model = models.resnet18()
  unsafe_model.load_state_dict(torch.load('model_weights.pth', weights_only=False))
  
  # Example of loading with map_location but no weights_only (should trigger B614)
  cpu_model = models.resnet18()
  cpu_model.load_state_dict(torch.load('model_weights.pth', map_location='cpu'))
  
  # Example of loading with both map_location and weights_only=True (should NOT trigger B614)
  safe_cpu_model = models.resnet18()
  safe_cpu_model.load_state_dict(torch.load('model_weights.pth', map_location='cpu', weights_only=True))
  