1.9 KiB
3-Model Merger Documentation
Add-Difference
A + (B - C) * α. This classic technique applies the "difference" between models B and C to model A. For example, it can be used to add a style (B) to a base model (A) while subtracting the style's original base (C).
Models Used: A, B, C Parameters:
- Alpha: A multiplier for the
(B - C)difference vector before it's added to A. - Beta: A smoothing toggle.
0for Off,1for On. When On, applies a median and gaussian filter to the difference, which can result in a smoother merge.
Train-Difference
A variation of Add-Difference from the SuperMerger extension that uses a more complex scaling factor based on the relative distances between the tensors of A, B, and C.
Models Used: A, B, C Parameters:
- Alpha: A multiplier for the final calculated "training" difference.
Extract-Features
A powerful mode that identifies features present in both
(B - A)and(C - A)and adds them to A. Allows for fine-grained control over combining aspects based on their similarity.
Models Used: A, B, C Parameters:
- Alpha: Weights the merge between Model B (
0.0) and Model C (1.0). - Beta: Controls the focus on similarity (
0.0) versus dissimilarity (1.0). - Gamma: A bias exponent for similarity. Higher values increase the bias.
- Delta: A final multiplier for the extracted features before they are added to Model A.
Add-Dissimilarities
Identifies features that are dissimilar between Model B and Model C and adds them to Model A. Useful for combining unique aspects of two different models.
Models Used: A, B, C Parameters:
- Alpha: Weights the comparison between Model B (
0.0) and Model C (1.0). - Beta: A multiplier for the final extracted dissimilar features.
- Gamma: A bias exponent for the similarity calculation.