,
...     height=768,
...     width=768,
...     num_inference_steps=100,
... ).images

>>> image[0].save("cat.png")  KandinskyCombinedPipeline  class diffusers.KandinskyCombinedPipeline  < source > ( text_encoder: MultilingualCLIP tokenizer: XLMRobertaTokenizer unet: UNet2DConditionModel scheduler: Union movq: VQModel prior_prior: PriorTransformer prior_image_encoder: CLIPVisionModelWithProjection prior_text_encoder: CLIPTextModelWithProjectio