Instructions to use neuralvfx/Z-Image-SAM-ControlNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use neuralvfx/Z-Image-SAM-ControlNet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("neuralvfx/Z-Image-SAM-ControlNet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "Tongyi-MAI/Z-Image", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -91,7 +91,7 @@ image = pipe(
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num_inference_steps=50,
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guidance_scale=4.0,
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controlnet_conditioning_scale=1.0,
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generator= torch.Generator("cuda").manual_seed(
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).images[0]
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image.save("output.png")
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num_inference_steps=50,
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guidance_scale=4.0,
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controlnet_conditioning_scale=1.0,
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generator= torch.Generator("cuda").manual_seed(45),
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).images[0]
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image.save("output.png")
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