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### Textual Inversion
To make use of pretrained embeddings, create an `embeddings` directory (in the same place as `webui.py`)
and put your embeddings into it. They must be .pt files, each with only one trained embedding,
and the filename (without .pt) will be the term you'll use in the prompt to get that embedding.
and put your embeddings into it. They must be either .pt or .bin files, each with only one trained embedding,
and the filename (without .pt/.bin) will be the term you'll use in the prompt to get that embedding.
As an example, I trained one for about 5000 steps: https://files.catbox.moe/e2ui6r.pt; it does not produce
very good results, but it does work. Download and rename it to Usada Pekora.pt, and put it into embeddings dir
and use Usada Pekora in prompt.
very good results, but it does work. To try it out download the file, rename it to `Usada Pekora.pt`, put it into the `embeddings` dir
and use `Usada Pekora` in the prompt.
You may also try some from the growing library of embeddings at https://huggingface.co/sd-concepts-library, downloading the `learned_embeds.bin` files, renaming them to the related term found in `token_identifier.txt` (without the < and >) and putting them in your `embeddings` directory.
You may also try some from the growing library of embeddings at https://huggingface.co/sd-concepts-library, downloading one of the `learned_embeds.bin` files, renaming it to the term you want to use for it in the prompt (be sure to keep the .bin extension) and putting it in your `embeddings` directory.
### How to change UI defaults?