Net, and it is trained on image-text and video-text datasets to enhance what it learns during training. The model takes a prompt, encodes it and creates text embeddings which are denoised by the UNet, and then decoded by a VQGAN into a video. ModelScopeT2V generates watermarked videos due to the datasets it was trained on. To use a watermark-free model, try the cerspense/zeroscope_v2_76w model with the TextToVideoSDPipeline first, and then upsc