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Shakker-Labs
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FLUX.1-dev-ControlNet-Union-Pro

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Diffusers
Safetensors
English
Text-to-Image
ControlNet
Diffusers
Flux.1-dev
image-generation
Stable Diffusion
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wanghaofan commited on
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Update README.md

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  1. README.md +3 -3
README.md CHANGED
@@ -54,7 +54,7 @@ from diffusers.utils import load_image
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  from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel
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  base_model = 'black-forest-labs/FLUX.1-dev'
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- controlnet_model_union = './Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro'
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  controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
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  controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend loading via FluxMultiControlNetModel
@@ -88,10 +88,10 @@ We also support loading multiple ControlNets as before, you can load as
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  ```python
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  from diffusers import FluxControlNetModel, FluxMultiControlNetModel
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- controlnet_model_union = './Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro'
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  controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
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- controlnet_model_depth = './Shakker-Labs/FLUX.1-dev-Controlnet-Depth'
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  controlnet_depth = FluxControlNetModel.from_pretrained(controlnet_model_depth, torch_dtype=torch.bfloat16)
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  controlnet = FluxMultiControlNetModel([controlnet_union, controlnet_depth])
 
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  from diffusers import FluxControlNetPipeline, FluxControlNetModel, FluxMultiControlNetModel
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  base_model = 'black-forest-labs/FLUX.1-dev'
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+ controlnet_model_union = 'Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro'
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  controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
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  controlnet = FluxMultiControlNetModel([controlnet_union]) # we always recommend loading via FluxMultiControlNetModel
 
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  ```python
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  from diffusers import FluxControlNetModel, FluxMultiControlNetModel
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+ controlnet_model_union = 'Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro'
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  controlnet_union = FluxControlNetModel.from_pretrained(controlnet_model_union, torch_dtype=torch.bfloat16)
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+ controlnet_model_depth = 'Shakker-Labs/FLUX.1-dev-Controlnet-Depth'
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  controlnet_depth = FluxControlNetModel.from_pretrained(controlnet_model_depth, torch_dtype=torch.bfloat16)
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  controlnet = FluxMultiControlNetModel([controlnet_union, controlnet_depth])