GitLab

This is an old model.

Load the checkpoint like a regular one and use the new
SD_4XUpscale_Conditioning node.

Let me know if this breaks anything.

To use it use the ImageOnlyCheckpointLoader to load the checkpoint and
the new Stable_Zero123 node.

comfy.ops -> comfy.ops.disable_weight_init

This should make it more clear what they actually do.

Some unused code has also been removed.

--fp8_e4m3fn-unet and --fp8_e5m2-unet are the two different formats
supported by pytorch.

Previously when a list of 3 images [0, 1, 2] was used for a 6 frame video
they were concated like this:
[0, 1, 2, 0, 1, 2]

now they are concated like this:
[0, 0, 1, 1, 2, 2]

apply_model in model_base now returns the denoised output.

This means that sampling_function now computes things on the denoised
output instead of the model output. This should make things more consistent
across current and future models.

The created checkpoints contain workflow metadata that can be loaded by
dragging them on top of the UI or loading them with the "Load" button.

Checkpoints will be saved in fp16 or fp32 depending on the format ComfyUI
is using for inference on your hardware. To force fp32 use: --force-fp32

Anything that patches the model weights like merging or loras will be
saved.

The output directory is currently set to: output/checkpoints but that might
change in the future.