The UNetCrossAttentionMultiply node applies multiplication factors to the cross-attention mechanism in a UNet model. It allows you to scale the query, key, value, and output components of the cross-attention layers to experiment with different attention behaviors and effects.

## Inputs

| Parameter | Description | Data Type | Required | Range |
| --- | --- | --- | --- | --- |
| `model` | The UNet model to modify with attention scaling factors | MODEL | Yes | - |
| `q` | Scaling factor for query components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `k` | Scaling factor for key components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `v` | Scaling factor for value components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |
| `out` | Scaling factor for output components in cross-attention (default: 1.0) | FLOAT | No | 0.0 - 10.0 |

## Outputs

| Output Name | Description | Data Type |
| --- | --- | --- |
| `model` | The modified UNet model with scaled cross-attention components | 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/UNetCrossAttentionMultiply/en.md)

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