runwayml/stable-diffusion-v1-5 are also compatible but they might be less performant. Make sure to check out the Stable Diffusion Tips section to learn how to explore the tradeoff between scheduler speed and quality, and how to reuse pipeline components efficiently! If you’re interested in using one of the official checkpoints for a task, explore the CompVis, Runway, and Stability AI Hub organizations!  StableDiffusionInpaintPipeline  class diffusers.StableDiffusionInpaintPipeline  < source > ( vae: Union text_encoder: CLIPTextModel tokenizer: CLIPTokenizer unet: UNet2DConditionModel scheduler: KarrasDiffusionSchedulers safety_checker: StableDiffusionSafetyChecker feature_extractor: CLIPImageProcessor image_encoder: CLIPVisionModelWithProjection = None requires_safety_checker: bool = True  )   Parameters   vae ([AutoencoderKL, AsymmetricAutoencoderKL]) —