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Enhances AI model performance by refining conditioning with selective output replacement based on skimming mask.
The Skimmed CFG
This parameter represents the AI model that will be patched with the skimming technique. The model is expected to be of type MODEL
. The node clones this model and applies the skimming patch to it, ensuring that the original model remains unaltered. This parameter is crucial as it provides the base on which the skimming technique will be applied.
The output of this node is a patched version of the input model. This patched model has the skimming technique applied to its conditioning process, which helps in generating outputs that are more aligned with the specified conditions. The patched model is returned as a tuple containing the modified model, ready to be used for further processing or sampling.
"AttributeError: 'NoneType' object has no attribute 'clone'"
None
.MODEL
and is not None
."RuntimeError: CUDA error: out of memory"
"TypeError: get_skimming_mask() missing 1 required positional argument"
get_skimming_mask
function is not receiving all the necessary arguments.get_skimming_mask
function within the node's implementation. Check for any missing parameters in the function call.© Copyright 2024 RunComfy. All Rights Reserved.
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