ion embedding vector which can be done via the TextualInversionLoaderMixin.load_textual_inversion
function. Here we’ll load the embeddings of the ”<cat-toy>” example from before.


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pipe.load_textual_inversion("sd-concepts-library/cat-toy")
Now we can run the pipeline making sure that the placeholder token <cat-toy> is used in our prompt.


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prompt = "A <cat-toy> backpack"

image = pipe(prompt, num_inference_steps=50).images[0]
im