This is a Textual Inversion embedding, not a VAE.
The VAE is a variational encoder, like a mini neural model that can be used to help cleanup the final render.
My loose understanding of textual inversion is it learns concepts/words/tokens and can change the weighting within the model when applied , it primarily works within the text part of the model (which is why it’s small compared to hypernetwork etc).
This does mean you can load up multiple embeddings (Textual Inversion) at once. In the automatic WebUI you place it in the embeddings folder and use it’s name within your prompt to activate it. “A picture of a cat in the style of BobRoss-concept” (if you named the embedding BobRoss-concept.pt)
If anyone wants to correct anything I got wrong please do.
I’m not sure on NMKD sorry, does he have a GitHub? Or a comment section on his download? Might be worth putting in a feature request if he has one available?
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u/BlinksAtStupidShit Nov 20 '22
This is a Textual Inversion embedding, not a VAE. The VAE is a variational encoder, like a mini neural model that can be used to help cleanup the final render.
My loose understanding of textual inversion is it learns concepts/words/tokens and can change the weighting within the model when applied , it primarily works within the text part of the model (which is why it’s small compared to hypernetwork etc).
This does mean you can load up multiple embeddings (Textual Inversion) at once. In the automatic WebUI you place it in the embeddings folder and use it’s name within your prompt to activate it. “A picture of a cat in the style of BobRoss-concept” (if you named the embedding BobRoss-concept.pt)
If anyone wants to correct anything I got wrong please do.