This documentation was AI-generated. If you find any errors or have suggestions for improvement, please feel free to contribute! Edit on GitHubThis node creates a hook model as a LoRA (Low-Rank Adaptation) by loading checkpoint weights and applying strength adjustments to both the model and CLIP components. It allows you to apply LoRA-style modifications to existing models through a hook-based approach, enabling fine-tuning and adaptation without permanent model changes. The node can combine with previous hooks and caches loaded weights for efficiency.
Inputs
| Parameter | Data Type | Required | Range | Description |
|---|---|---|---|---|
ckpt_name | COMBO | Yes | Multiple options available | The checkpoint file to load weights from (select from available checkpoints) |
strength_model | FLOAT | Yes | -20.0 to 20.0 | The strength multiplier applied to the model weights (default: 1.0) |
strength_clip | FLOAT | Yes | -20.0 to 20.0 | The strength multiplier applied to the CLIP weights (default: 1.0) |
prev_hooks | HOOKS | No | - | Optional previous hooks to combine with the newly created LoRA hooks |
- The
ckpt_nameparameter loads checkpoints from the available checkpoints folder - Both strength parameters accept values from -20.0 to 20.0 with 0.01 step increments
- When
prev_hooksis not provided, the node creates a new hook group - The node caches loaded weights to avoid reloading the same checkpoint multiple times
Outputs
| Output Name | Data Type | Description |
|---|---|---|
HOOKS | HOOKS | The created LoRA hooks, combined with any previous hooks if provided |