library implements for all the pipelines (such as downloading or saving, running on a particular device, etc.) The pipeline also inherits the following loading methods: load_textual_inversion() for loading textual inversion embeddings from_single_file() for loading .ckpt files load_lora_weights() for loading LoRA weights save_lora_weights() for saving LoRA weights  __call__  < source > ( prompt: Union = None prompt_2: Union = None image: Union = None height: Optional = None width: Optional = None num_inference_steps: int = 100 denoising_end: Optional = None guidance_scale: float = 5.0 image_guidance_scale: float = 1.5 negative_prompt: Union = None negative_prompt_2: Union = None num_images_per_prompt: Optional = 1 eta: float = 0.0 generator: Union = None latents: Optional = None prompt_embeds: Optional = None negative_prompt_embeds: Optional = None pooled_prompt_embeds: Optional = None negative_pooled_prompt_embeds: Optional = None output_type: Optional = 'pil' return_dict: bool = True callback: Optional = None callback_steps: int = 1 cross_attention_kwargs: Optional = None guidance_rescale: float = 0.0 original_size: Tuple = None crops_coords_top_left: Tuple = (0, 0) target_size: Tuple = None  ) → ~pipelines.stable_diffusion_xl.StableDiffusionXLPipelineOutput or tuple  Parameters   prompt (str or List[str], optional) —