l_inversion()
LoRA: loaders.LoraLoaderMixin.load_lora_weights()
as well as the following saving methods:
LoRA: loaders.LoraLoaderMixin.save_lora_weights()

__call__

<
source
>
(
prompt: typing.Union[str, typing.List[str]] = None
image: typing.Union[torch.FloatTensor, PIL.Image.Image] = None
num_inference_steps: int = 100
guidance_scale: float = 7.5
image_guidance_scale: float = 1.5
negative_prompt: typing.Union[str, typing.List[str], NoneType]