Instructions to use Tencent-Hunyuan/HunyuanDiT-v1.2-ControlNet-Diffusers-Pose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Tencent-Hunyuan/HunyuanDiT-v1.2-ControlNet-Diffusers-Pose with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.2-ControlNet-Diffusers-Pose", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -9,7 +9,7 @@ from diffusers import HunyuanDiT2DControlNetModel, HunyuanDiTControlNetPipeline
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import torch
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controlnet = HunyuanDiT2DControlNetModel.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.2-ControlNet-Diffusers-
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pipe = HunyuanDiTControlNetPipeline.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers-Distilled", controlnet=controlnet, torch_dtype=torch.float16)
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pipe.to("cuda")
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import torch
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controlnet = HunyuanDiT2DControlNetModel.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.2-ControlNet-Diffusers-Pose", torch_dtype=torch.float16)
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pipe = HunyuanDiTControlNetPipeline.from_pretrained("Tencent-Hunyuan/HunyuanDiT-v1.2-Diffusers-Distilled", controlnet=controlnet, torch_dtype=torch.float16)
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pipe.to("cuda")
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