ps=100,
... ).images

>>> image[0].save("cat.png")  interpolate  < source > ( images_and_prompts: List weights: List num_images_per_prompt: int = 1 num_inference_steps: int = 25 generator: Union = None latents: Optional = None negative_prior_prompt: Optional = None negative_prompt: str = '' guidance_scale: float = 4.0 device = None  ) → KandinskyPriorPipelineOutput or tuple  Parameters   images_and_prompts (List[Union[str, PIL.Image.Image, torc