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* first draft * remove old loader doc * start adding lora code examples * finish * add link to loralinearlayer * feedback * fix
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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
autodoc loaders.textual_inversion.TextualInversionLoaderMixin