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clarify that add_lcm_lora can load SDXL-Lightning
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@ -26,23 +26,24 @@ def add_lcm_lora(
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manager: SDLoraManager,
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manager: SDLoraManager,
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tensors: dict[str, torch.Tensor],
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tensors: dict[str, torch.Tensor],
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name: str = "lcm",
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name: str = "lcm",
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scale: float = 1.0 / 8.0,
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scale: float = 8.0 / 64.0,
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check_validity: bool = True,
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check_validity: bool = True,
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) -> None:
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) -> None:
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"""Add a LCM LoRA to SDXLUNet.
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"""Add a [LCM-LoRA](https://arxiv.org/abs/2311.05556) or a LoRA with similar structure
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such as [SDXL-Lightning](https://arxiv.org/abs/2402.13929) to SDXLUNet.
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This is a complex LoRA so [SDLoraManager.add_loras()][refiners.foundationals.latent_diffusion.lora.SDLoraManager.add_loras]
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This is a complex LoRA so [SDLoraManager.add_loras()][refiners.foundationals.latent_diffusion.lora.SDLoraManager.add_loras]
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is not enough. Instead, we add the LoRAs to the UNet in several iterations, using the filtering mechanism of
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is not enough. Instead, we add the LoRAs to the UNet in several iterations, using the filtering mechanism of
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[auto_attach_loras][refiners.fluxion.adapters.lora.auto_attach_loras].
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[auto_attach_loras][refiners.fluxion.adapters.lora.auto_attach_loras].
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This LoRA can be used with or without CFG in SD.
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LCM-LoRA can be used with or without CFG in SD.
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If you use CFG, typical values range from 1.0 (same as no CFG) to 2.0.
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If you use CFG, typical values range from 1.0 (same as no CFG) to 2.0.
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Args:
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Args:
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manager: A SDLoraManager for SDXL
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manager: A SDLoraManager for SDXL.
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tensors: The `state_dict` of the LCM LoRA
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tensors: The `state_dict` of the LoRA.
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name: The name of the LoRA.
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name: The name of the LoRA.
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scale: The scale to use for the LoRA (should generally not be changed).
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scale: The scale to use for the LoRA (should generally not be changed, those LoRAs must use alpha / rank).
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check_validity: Perform additional checks, raise an exception if they fail.
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check_validity: Perform additional checks, raise an exception if they fail.
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"""
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"""
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