An implementation of adaptive guidance for ComfyUI
See https://bcv-uniandes.github.io/adaptiveguidance-wp/
There's an AdaptiveGuidance node (under sampling/custom_sampling/guiders) that can be used with SamplerCustomAdvanced. Normally, you should keep the threshold quite high, between 0.99 and 1.0
The node calculates the cosine similarity between the u-net's conditional and unconditional output ("positive" and "negative" prompts) and once the similarity crosses the specified threshold, it sets CFG to 1.0, effectively skipping negative prompt calculations and speeding up inference.
I'm not sure if the cosine similarity calculation matches the original paper since I had to translate from maths to Python, but it appears to work.
Set uncond_zero_scale to > 0 to enable "uncond zero" CFG after the normal CFG gets disabled. Stolen from https://github.com/Extraltodeus/Uncond-Zero-for-ComfyUI
It seems to work slightly better than just running without CFG, but YMMV
Note: this functionality is unstable and will probably change, so using it means your workflows likely won't be perfectly reproducible.