Textual Inversion Textual Inversion is a training method for personalizing models by learning new text embeddings from a few example images. The file produced from training is extremely small (a few KBs) and the new embeddings can be loaded into the text encoder. TextualInversionLoaderMixin provides a function for loading Textual Inversion embeddings from Diffusers and Automatic1111 into the text encoder and loading a special token to activate the embeddings. To learn more about how to load Textual Inversion embeddings, see the Textual Inversion loading guide.  TextualInversionLoaderMixin  class diffusers.loaders.TextualInversionLoaderMixin  < source > ( )    Load Textual Inversion tokens and embeddings to the tokenizer and text encoder.  load_textual_inversion  < source > ( pretrained_model_name_or_path: Union token: Union = None tokenizer: Optional = None text_encoder: Optional = None **kwargs  )   Parameters   pretrained_model_name_or_path (str or os.PathLike or List[str or os.PathLike] or Dict or List[Dict]) —