Update README.md

2024-04-15 08:50:47 +02:00
parent 9ab14842dc
commit 3bd5b34829
1 changed files with 1 additions and 1 deletions
@@ -11,7 +11,7 @@ Updated:
 15.04.24

 - Added "no uncond" node which completely disable the negative and doubles the speed while rescaling the latent space in the post-cfg function up until the sigmas are at 1. By itself it is not perfect and I'm searching for solutions to improve the final result. It seems to work better with dpmpp3m_sde/exponential if you're not using anything else. If you are using the PAG node then you don't need to care about the sampler but will generate at a normal speed. Result will be simply different (I personally like them).
- To use the [PAG node](https://github.com/pamparamm/sd-perturbed-attention/tree/master) without slow-down (if using the no-uncond node) or at least take advantage of the boost feature:
+- To use the [PAG node](https://github.com/pamparamm/sd-perturbed-attention/tree/master) without the complete slow-down (if using the no-uncond node) or at least take advantage of the boost feature:
  - in the "pag_nodes.py" file look for "disable_cfg1_optimization=True"
  - set it to "disable_cfg1_optimization=False".
 - For the negative lerp function in the other nodes the scale has been divided by two. So if you were using it at 10, set it to 5.