> ## Documentation Index
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# ModelSamplingAuraFlow - ComfyUI Built-in Node Documentation

> The ModelSamplingAuraFlow node applies a specialized sampling configuration to diffusion models, specifically designed for AuraFlow model architectures.

The ModelSamplingAuraFlow node applies a specialized sampling configuration to diffusion models, specifically designed for AuraFlow model architectures. It modifies the model's sampling behavior by applying a shift value that adjusts the sampling distribution. This node inherits from the SD3 model sampling framework and provides fine control over the sampling process.

## Inputs

| Parameter  | Description                                                                                     | Data Type | Required | Range                                |
| ---------- | ----------------------------------------------------------------------------------------------- | --------- | -------- | ------------------------------------ |
| `model`    | The diffusion model to apply the AuraFlow sampling configuration to                             | MODEL     | Yes      | -                                    |
| `shift`    | The shift value to apply to the sampling distribution (default: 1.73, step: 0.01)               | FLOAT     | Yes      | 0.0 - 100.0                          |
| `sampling` | The sampling mode used when patching the model (default: "flow"). Marked as an advanced option. | COMBO     | No       | "flow"<br />"img\_to\_img\_velocity" |

## Outputs

| Output Name | Description                                                     | Data Type |
| ----------- | --------------------------------------------------------------- | --------- |
| `model`     | The modified model with AuraFlow sampling configuration 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/ModelSamplingAuraFlow/en.md)

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