Krea2 Model Patcher

Patches the Krea2 native text-to-image model with a trained image-adapter so it can accept reference-image conditioning alongside a text prompt.

Background

Krea2 is a diffusion model released by Krea AI. This adapter was trained on semi-synthetic data — organic target images paired with synthetic reference images and prompts — to teach the model to follow reference imagery while still obeying text instructions. The adapter injects reference information via RoPE encoding, enabling the model to attend to up to 4 reference images at once.

Inputs

Name	Type	Description
`model`	MODEL	The loaded Krea2 base model.
`patch_path`	STRING	Path to the adapter safetensors file (e.g. `krea2_image_adapter_v1_000001500.safetensors`). Relative paths resolve from the ComfyUI root.

Outputs

Name	Type	Description
`model`	MODEL	The patched Krea2 model, ready to consume reference conditioning.

Usage

Load the Krea2 checkpoint with a Load Diffusion Model node.
Connect its MODEL output to this node.
Set patch_path to the location of the adapter weights.
Wire the patched MODEL into a sampler (e.g. KSampler).
Pair with Krea2 Reference Encoder to supply the actual reference images.

Notes

This node must be used with the Krea2 base model. Using it with an unrelated checkpoint will produce undefined behaviour.
The adapter is applied at full strength (1.0). Strength control may be added in a future version.
Without a Krea2 Reference Encoder connected downstream, the patched model behaves identically to the unpatched base model.

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