Update README.md
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@@ -19,7 +19,7 @@ All are to be used like any model patching node, right after the model loader.
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Named like this because I initially wanted to test what would happen if I used, instead of a single CFG scale, a tensor shaped like the latent space with a gradual variation. Then why not try to use masks instead? And what if I could make it so each value will participate so the image would match as close as possible to an input image?
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The result is an arithmetic scaling method which does not noticeably slow down the sampling while also scaling the intensity of the values during the sampling.
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The result is an arithmetic scaling method which does not noticeably slow down the sampling while also scaling the intensity of the values like an "automatic cfg".
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So here it is:
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