Unverified Commit 13f388ee authored by exo-pla-net's avatar exo-pla-net Committed by GitHub
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Improve documentation for the LPW pipeline (#1182)

parent af279434
...@@ -179,9 +179,20 @@ images = pipe.inpaint(prompt=prompt, init_image=init_image, mask_image=mask_imag ...@@ -179,9 +179,20 @@ images = pipe.inpaint(prompt=prompt, init_image=init_image, mask_image=mask_imag
As shown above this one pipeline can run all both "text-to-image", "image-to-image", and "inpainting" in one pipeline. As shown above this one pipeline can run all both "text-to-image", "image-to-image", and "inpainting" in one pipeline.
### Long Prompt Weighting Stable Diffusion ### Long Prompt Weighting Stable Diffusion
Features of this custom pipeline:
The Pipeline lets you input prompt without 77 token length limit. And you can increase words weighting by using "()" or decrease words weighting by using "[]" - Input a prompt without the 77 token length limit.
The Pipeline also lets you use the main use cases of the stable diffusion pipeline in a single class. - Includes tx2img, img2img. and inpainting pipelines.
- Emphasize/weigh part of your prompt with parentheses as so: `a baby deer with (big eyes)`
- De-emphasize part of your prompt as so: `a [baby] deer with big eyes`
- Precisely weigh part of your prompt as so: `a baby deer with (big eyes:1.3)`
Prompt weighting equivalents:
- `a baby deer with` == `(a baby deer with:1.0)`
- `(big eyes)` == `(big eyes:1.1)`
- `((big eyes))` == `(big eyes:1.21)`
- `[big eyes]` == `(big eyes:0.91)`
You can run this custom pipeline as so:
#### pytorch #### pytorch
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