W.A.L.T is a real-time video generation method based on transformers, which achieves cross-modal training and generation by jointly compressing images and videos into a unified latent space. It employs window-based attention mechanisms to enhance memory usage and training efficiency. This approach has achieved state-of-the-art performance in various video and image generation benchmark tests.