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fix miscellaneous typos
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@ -364,7 +364,7 @@ python scripts/conversion/convert_diffusers_ip_adapter.py --from ip-adapter-plus
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This will download and convert both IP-Adapter and CLIP Image Encoder pretrained weights.
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Then, in your Python code, simply instantiate a [`SDXLIPAdapter`][refiners.foundationals.latent_diffusion.stable_diffusion_xl.image_prompt.SDXLIPAdapter] targetting our `sdxl.unet`, and inject it using a simple `.inject()` call:
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Then, in your Python code, simply instantiate a [`SDXLIPAdapter`][refiners.foundationals.latent_diffusion.stable_diffusion_xl.image_prompt.SDXLIPAdapter] targeting our `sdxl.unet`, and inject it using a simple `.inject()` call:
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```py
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# IP-Adapter
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@ -55,7 +55,7 @@ class Chain(ContextModule):
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This layer is the main building block of Fluxion.
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It is used to compose other layers in a sequential manner.
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Similary to [`torch.nn.Sequential`][torch.nn.Sequential],
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Similarly to [`torch.nn.Sequential`][torch.nn.Sequential],
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it calls each of its sub-layers in order, chaining their outputs as inputs to the next sublayer.
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However, it also provides additional methods to manipulate its sub-layers and their context.
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@ -131,7 +131,7 @@ class SDLoraManager:
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SDLoraManager.auto_attach(unet_loras, self.unet, exclude=exclude)
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def remove_loras(self, *names: str) -> None:
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"""Remove mulitple LoRAs from the target.
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"""Remove multiple LoRAs from the target.
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Args:
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names: The names of the LoRAs to remove.
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@ -179,7 +179,7 @@ class SDLoraManager:
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self.update_scales({name: scale})
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def update_scales(self, scales: dict[str, float], /) -> None:
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"""Update the scales of mulitple LoRAs.
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"""Update the scales of multiple LoRAs.
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Args:
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scales: The scales to update.
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