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# RenormCFG - ComfyUI Built-in Node Documentation

> The RenormCFG node modifies the classifier-free guidance (CFG) process in diffusion models by applying conditional scaling and normalization.

The RenormCFG node modifies the classifier-free guidance (CFG) process in diffusion models by applying conditional scaling and normalization. It adjusts the denoising process based on a specified timestep threshold and a renormalization factor, controlling the influence of conditional versus unconditional predictions during image generation. The resulting model is returned with this patched CFG behavior.

## Inputs

| Parameter    | Description                                                                                                                                                                                                  | Data Type | Required | Range                   |
| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------- | -------- | ----------------------- |
| `model`      | The diffusion model to apply renormalized CFG to                                                                                                                                                             | MODEL     | Yes      | -                       |
| `cfg_trunc`  | Timestep threshold for applying CFG scaling. When the current timestep is below this value, CFG scaling and renormalization are applied; otherwise, only the conditional prediction is used (default: 100.0) | FLOAT     | No       | 0.0 - 100.0 (step 0.01) |
| `renorm_cfg` | Renormalization factor that limits the maximum norm of the CFG-scaled prediction relative to the original conditional prediction. A value of 0.0 disables renormalization (default: 1.0)                     | FLOAT     | No       | 0.0 - 100.0 (step 0.01) |

Note: `cfg_trunc` and `renorm_cfg` are advanced parameters. Renormalization only takes effect when `renorm_cfg` is greater than 0.0 and the current timestep is below `cfg_trunc`; if the new prediction norm is already below the computed maximum, no rescaling is performed.

## Outputs

| Output Name | Description                                                   | Data Type |
| ----------- | ------------------------------------------------------------- | --------- |
| `model`     | The modified model with the renormalized CFG function applied | MODEL     |

> This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! [Edit on GitHub](https://github.com/Comfy-Org/embedded-docs/blob/main/comfyui_embedded_docs/docs/RenormCFG/en.md)

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