+ pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)  Low-memory Video generation is very memory intensive as we have to essentially generate num_frames all at once. The mechanism is very comparable to text-to-image generation with a high batch size. To reduce the memory requirement you have multiple options. The following options trade inference speed against lower memory requirement: enable model offloading: Each component of the pipeline is offloaded to CPU once it’s not needed anymore. enable feed-forward chunking: The feed-forward layer runs in a loop instead of running with a single huge feed-forward batch size reduce decode_chunk_size: This means that the VAE decodes frames in chunks instead of decoding them all together. Note: In addition to leading to a small slowdown, this method also slightly leads to video quality deterioration You can enable them as follows:   Copied -pipe.enable_model_cpu_offload()