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The TomePatchModel node applies Token Merging (ToMe) to a diffusion model to reduce computational requirements during inference. It works by selectively merging similar tokens in the attention mechanism, allowing the model to process fewer tokens while maintaining image quality. This technique helps speed up generation without significant quality loss.

Inputs

ParameterDescriptionData TypeRequiredRange
modelThe diffusion model to apply token merging toMODELYes-
ratioThe ratio of tokens to merge (default: 0.3). Higher values merge more tokens, resulting in greater speedup but potentially lower quality.FLOATYes0.0 - 1.0

Outputs

Output NameDescriptionData Type
modelThe modified model with token merging appliedMODEL
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