Auto-MBW for ComfyUI loosely based on sdweb-auto-MBW
Purpose
This node "advanced > auto merge block weighted" takes two models, merges individual blocks together at various ratios, and automatically rates each merge, keeping the ratio with the highest score. Whether this is a good idea or not is anyone's guess. In practice this makes models that make images the classifier says are good.
Settings
- Prompt: to generate sample images to be rated
- Sample Count: number of samples per ratio per block to generate
- Search Depth: number of branches to take while choosing ratios to test
- Classifier: model used to rate images
Search Depth
To calculate ratios to test, the node branches out from powers of 0.5
- A depth of 2 will examine 0.0, 0.5, 1.0
- A depth of 4 will examine 0.0, 0.125, 0.25, 0.375, 0.5, 0.625, 0.75, 0.875, 1.0
- A depth of 6 will examine 33 different ratios
Classifier
The classifier models have been taken from the sdweb-auto-MBW repo
Notes
- --highvram flag recommended - both models will be kept in VRAM and the process is much faster
- many hardcoded settings are arbitrary - such as the sampler and block processing order
- generated images are not saved
- the final model is saved in the models/checkpoints directory with a timestamped name
- the resulting model will contain the text encoder and VAE sent to the node, without modification.