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Enhances AI art conditioning by combining unmasked data with existing data for richer, nuanced outputs.
The ADE_PairedConditioningSetUnmaskedAndCombine node is designed to enhance the conditioning process in AI art generation by combining existing conditioning data with new, unmasked conditioning data. This node is particularly useful for scenarios where you want to merge two sets of conditioning data without applying any masks, allowing for a more straightforward and unaltered combination. By leveraging this node, you can ensure that the conditioning data retains its original characteristics while still benefiting from the additional information provided by the new conditioning data. This can be especially beneficial in creating more nuanced and detailed AI-generated art, as it allows for a richer and more complex conditioning input.
This parameter represents the existing positive conditioning data that you want to combine with new conditioning data. It is crucial for defining the initial state of the positive conditioning before any new data is added.
This parameter represents the existing negative conditioning data that you want to combine with new conditioning data. It is essential for defining the initial state of the negative conditioning before any new data is added.
This parameter represents the new positive conditioning data that will be combined with the existing positive conditioning data. It serves as the additional information that will be merged to enhance the positive conditioning.
This parameter represents the new negative conditioning data that will be combined with the existing negative conditioning data. It serves as the additional information that will be merged to enhance the negative conditioning.
This optional parameter allows you to apply a LoRA (Low-Rank Adaptation) hook to the new conditioning data before combining it with the existing data. This can be useful for fine-tuning the conditioning data to better suit specific needs or preferences.
This output parameter provides the final combined positive conditioning data. It represents the result of merging the existing positive conditioning with the new positive conditioning data, potentially enhanced by any applied LoRA hooks.
This output parameter provides the final combined negative conditioning data. It represents the result of merging the existing negative conditioning with the new negative conditioning data, potentially enhanced by any applied LoRA hooks.
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