Register Model as LoRA Hook (MO) 🎭🅐🅓¶
Documentation¶
- Class name:
ADE_RegisterModelAsLoraHookModelOnly
- Category:
Animate Diff 🎭🅐🅓/conditioning/register lora hooks
- Output node:
False
This node specializes in registering a model as a LoRA hook with a focus on model-only modifications. It enables the integration of LoRA (Low-Rank Adaptation) techniques into a specific model, enhancing its adaptability and performance for specific tasks without affecting other components.
Input types¶
Required¶
model
- The model to be adapted using LoRA techniques. It serves as the primary target for the application of low-rank adaptations, aiming to enhance its performance or adaptability for specific tasks.
- Comfy dtype:
MODEL
- Python dtype:
ModelPatcher
ckpt_name
- The name of the checkpoint to apply LoRA configurations from. This parameter specifies which set of LoRA adaptations to use, guiding the customization of the model's behavior.
- Comfy dtype:
COMBO[STRING]
- Python dtype:
str
strength_model
- A floating-point value that determines the intensity of the LoRA adaptation on the model. It modulates how significantly the LoRA parameters influence the model's behavior.
- Comfy dtype:
FLOAT
- Python dtype:
float
Output types¶
model
- Comfy dtype:
MODEL
- The model after applying the specified LoRA adaptations. This output reflects the enhanced or customized version of the model, tailored through the LoRA technique.
- Python dtype:
ModelPatcher
- Comfy dtype:
lora_hook
- Comfy dtype:
LORA_HOOK
- A reference to the LoRA hook that has been integrated into the model. This output provides access to the LoRA adaptations applied, facilitating further manipulations or analyses.
- Python dtype:
LoraHook
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes: unknown
Source code¶
class MaskableSDModelLoaderModelOnly(MaskableSDModelLoader):
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model": ("MODEL",),
"ckpt_name": (folder_paths.get_filename_list("checkpoints"), ),
"strength_model": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}),
}
}
RETURN_TYPES = ("MODEL", "LORA_HOOK")
CATEGORY = "Animate Diff 🎭🅐🅓/conditioning/register lora hooks"
FUNCTION = "load_model_as_lora_model_only"
def load_model_as_lora_model_only(self, model: ModelPatcher, ckpt_name: str, strength_model: float):
model_lora, clip_lora, lora_hook = self.load_model_as_lora(model=model, clip=None, ckpt_name=ckpt_name,
strength_model=strength_model, strength_clip=0)
return (model_lora, lora_hook)