The CLIP patch ignores the connections and patches the model within the memory. Simply disconnecting it does not revert the behavior. To revert to default behavior set it at 1 or reload the model without the node connected. It is the only node ignoring the connections and does not modify anything but the connected CLIP model.
For SD1 and SDXL nodes: settings the temperature at zero will use a dynamic scale proportional to the resolution. It is good for lower resolutions but not on point for higher.

Requirements

Requires pytorch 2.3 and above.

Usage

Like any other model patch:

Pay attention to not use SD1 nodes on SDXL and vice-versa or you will get a key not found error.

Interesting side-effect:

Changing the UNET temperature allows to obtain better results a different resolutions. While it is not the full solution to the scaling issues of Stable Diffusion, it is a strong clue indicating the possibility to sample at much higher (or lower) resolutions.

Examples

Here using SDXL at a resolution of 328x328. First row temperature at 1, second row using dynamic scaled attention:

Non cherry-picked SD v1-5-pruned-emaonly at 512*1024, first row with the dynamic scale, second without:

Lost workflows for these as they were done during testing but proves the idea of making SD better at different resolutions:

The temperature was applied to all layers except input 1 and 2, output 9, 10 and 11. At 0.71. Only on self-attention. Using SD v1-5-pruned-emaonly. Resolution at 1024*512. The temperature matches 1/2**2 and the surface is double the normal resolution.

Patreon

Give an incentive to contributors:

https://www.patreon.com/extraltodeus