59 lines
2.1 KiB
Markdown
59 lines
2.1 KiB
Markdown
---
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tags:
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- LoRA
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---
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# LoraLoaderModelOnly
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## Documentation
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- Class name: `LoraLoaderModelOnly`
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- Category: `loaders`
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- Output node: `False`
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This node specializes in loading a LoRA model without requiring a CLIP model, focusing on enhancing or modifying a given model based on LoRA parameters. It allows for the dynamic adjustment of the model's strength through LoRA parameters, facilitating fine-tuned control over the model's behavior.
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## Input types
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### Required
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- **`model`**
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- The model to which LoRA adjustments will be applied. It serves as the base for modifications.
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- Comfy dtype: `MODEL`
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- Python dtype: `torch.nn.Module`
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- **`lora_name`**
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- The name of the LoRA file to be loaded. This specifies which LoRA adjustments to apply to the model.
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- Comfy dtype: `COMBO[STRING]`
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- Python dtype: `str`
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- **`strength_model`**
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- Determines the intensity of the LoRA adjustments applied to the model. A higher value indicates stronger modifications.
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- Comfy dtype: `FLOAT`
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- Python dtype: `float`
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## Output types
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- **`model`**
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- Comfy dtype: `MODEL`
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- The modified model with LoRA adjustments applied, reflecting changes in model behavior or capabilities.
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- Python dtype: `torch.nn.Module`
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## Usage tips
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- Infra type: `GPU`
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- Common nodes:
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- IPAdapterApplyFaceID
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- [LoraLoaderModelOnly](../../Comfy/Nodes/LoraLoaderModelOnly.md)
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- [KSampler](../../Comfy/Nodes/KSampler.md)
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- [FreeU_V2](../../Comfy/Nodes/FreeU_V2.md)
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- [UltimateSDUpscale](../../ComfyUI_UltimateSDUpscale/Nodes/UltimateSDUpscale.md)
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## Source code
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```python
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class LoraLoaderModelOnly(LoraLoader):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "model": ("MODEL",),
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"lora_name": (folder_paths.get_filename_list("loras"), ),
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"strength_model": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}),
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}}
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RETURN_TYPES = ("MODEL",)
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FUNCTION = "load_lora_model_only"
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def load_lora_model_only(self, model, lora_name, strength_model):
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return (self.load_lora(model, None, lora_name, strength_model, 0)[0],)
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```
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