Is ViT better than ResNet?

Could you elaborate on why you're asking if Vision Transformer (ViT) is better than Residual Network (ResNet)? Both models have their unique strengths and are suitable for different tasks in computer vision. ViT, for instance, excels at capturing global context and long-range dependencies, while ResNet is known for its ability to handle complex patterns and deep hierarchical representations. Are you looking for a model that can achieve better performance on a specific task, or are you interested in understanding the fundamental differences between the two architectures?