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Merge-Stable-Diffusion-models-without-distortion-gui
Implementation: https://github.com/samuela/git-re-basin
- I'm testing if the 1.5 and 2.0 model combine in Automatic 1111 now...
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I love SD but the pain is real
Wouldn't "applying the permutation" simply swap all the parameters in a model so they match on both models? For example, in https://github.com/samuela/git-re-basin/blob/main/src/cifar10_vgg_weight_matching.py, on line 184 they apply the permutation, and on line 192 they lerp from model A's params to the permuted model B's params. This lerp is basically a weighted sum merge, isn't it? At a lerp of 0.5, it would be somewhere in between model A and the permuted model B.
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Not really working, poorly coded sparse tensor compression of Dreambooth models. Help appreciated, code in comments
Definitely interesting, but you might get something useful out of https://github.com/samuela/git-re-basin ?
- Git Re-Basin: Merging models and preserving latent spaces (ie not the A111 linear interpolation)
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Most Popular AI Research Sept 2022 - Ranked Based On Total GitHub Stars
Git Re-Basin: Merging Models modulo Permutation Symmetries https://github.com/samuela/git-re-basin https://arxiv.org/abs/2209.04836v1
- [D] Most Popular AI Research Sept 2022 - Ranked Based On GitHub Stars
- Git Re-Basin: Merging Models Modulo Permutation Symmetries
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A note from our sponsor - WorkOS
workos.com | 25 Apr 2024
Stats
samuela/git-re-basin is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of git-re-basin is Python.
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