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Description
Is your feature request related to a problem? Please describe.
It is frustrating to load Textual Inversion embeddings on SD pipelines, adds bloat to the code. It would be good if we could just pipeline.load_embeddings
and add new embeddings ad-hoc to the pipeline.
Describe the solution you'd like
I would like to implement a method on Stable Diffusion pipelines to let people load_embeddings
and append them to ones from the text encoder and tokenizer, something like:
pipeline.load_embeddings({"emb1": "emb1.ckpt"})
, then- Embedding is loaded and appended to the embedding matrix of text encoder. Token is added to tokenizer.
- Predictions work with the new token smoothly.
We could even hack a way to load tokens with multiple embedding columns, alike to what we can do on Auto1111.
Describe alternatives you've considered
- Do that by hand every single time, but then if would bloat my code and wouldn't benefit the Diffusers community
- Don't use textual inversion at all, but this would be no-fun.
Additional context
I can implement it and open a PR if you approve the idea.
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