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AUTOMATIC1111 2022-09-30 16:57:10 +03:00
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Features.md

@ -159,23 +159,13 @@ Here's are settings that create the graph above:
![](images/xy_grid-medusa-ui.png)
# Textual Inversion
Allows you to use pretrained textual inversion embeddings.
See original site for details: https://textual-inversion.github.io/.
I used lstein's repo for training embdedding: https://github.com/lstein/stable-diffusion; if
you want to train your own, I recommend following the guide on his site.
See original site for details about what textual inversion is: https://textual-inversion.github.io/.
Update: you can now download many pre-trained embeddings from this page: https://huggingface.co/sd-concepts-library
Short explanation: place your embeddings into `embeddings` directory, and use the filename in prompt.
To make use of pretrained embeddings, create `embeddings` directory in the same directory as `webui.py`
and put your embeddings into it. They must be .pt or .bin files about 5Kb in size, each with only
one trained embedding, and the filename (without .pt or .bin) will be the term you'd use in prompt
to get that embedding.
Long explanation: [Textual Inversion](Textual-Inversion)
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.
![](images/inversion.png)
![grid-0037](https://user-images.githubusercontent.com/20920490/193285770-9454c5e1-e594-463c-8be8-1488ddf2877b.png)
# Resizing
There are three options for resizing input images in img2img mode: