2023-04-20 18:14:37 -04:00
2023-04-20 17:51:10 -04:00
2023-04-20 17:30:05 -04:00
2023-04-20 18:14:37 -04:00

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

Currently this only supports cafeai "aesthetic" and "waifu" models.

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.
S
Description
No description provided
Readme
3.9 MiB
Languages
Python 100%