Update README.md
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README.md
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@@ -37,7 +37,6 @@ from PIL import Image
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from diffusers import StableDiffusionControlNetPipeline, UNet2DConditionModel, UniPCMultistepScheduler
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import torch
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from PIL import Image
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from diffusers.utils import load_image
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from models.controllora import ControlLoRAModel
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image = Image.open('<Your Conditioning Image Path>')
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@@ -45,13 +44,13 @@ image = Image.open('<Your Conditioning Image Path>')
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unet = UNet2DConditionModel.from_pretrained(
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"runwayml/stable-diffusion-v1-5", subfolder="unet"
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)
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controllora =
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"HighCWu/HighCWu/sd-controllora-face-landmarks", torch_dtype=torch.float16
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)
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controllora.tie_weights(unet)
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", unet=unet, controlnet=
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)
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pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
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from diffusers import StableDiffusionControlNetPipeline, UNet2DConditionModel, UniPCMultistepScheduler
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import torch
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from PIL import Image
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from models.controllora import ControlLoRAModel
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image = Image.open('<Your Conditioning Image Path>')
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unet = UNet2DConditionModel.from_pretrained(
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"runwayml/stable-diffusion-v1-5", subfolder="unet"
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)
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controllora = ControlLoRAModel.from_pretrained(
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"HighCWu/HighCWu/sd-controllora-face-landmarks", torch_dtype=torch.float16
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)
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controllora.tie_weights(unet)
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pipe = StableDiffusionControlNetPipeline.from_pretrained(
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"runwayml/stable-diffusion-v1-5", unet=unet, controlnet=controllora, safety_checker=None, torch_dtype=torch.float16
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)
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pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
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