           Tips Video generation is memory-intensive and one way to reduce your memory usage is to set enable_forward_chunking on the pipeline’s UNet so you don’t run the entire feedforward layer at once. Breaking it up into chunks in a loop is more efficient. Check out the Text or image-to-video guide for more details about how certain parameters can affect video generation and how to optimize inference by reducing memory usage. Make sure to check out the Schedulers guide to learn how to explore the tradeoff between scheduler speed and quality, and see the reuse components across pipelines section to learn how to efficiently load the same components into multiple pipelines.  TextToVideoSDPipeline  class diffusers.TextToVideoSDPipeline  < source > ( vae: AutoencoderKL text_encoder: CLIPTextModel tokenizer: CLIPTokenizer unet: UNet3DConditionModel scheduler: KarrasDiffusionSchedulers  )   Parameters   vae (AutoencoderKL) —