Instructions to use alimama-creative/SD3-Controlnet-Inpainting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alimama-creative/SD3-Controlnet-Inpainting with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alimama-creative/SD3-Controlnet-Inpainting", 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
- Local Apps
- Draw Things
- DiffusionBee
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README.md
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# Load image
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image = load_image(
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"https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/
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mask = load_image(
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"https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/
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# Set args
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width = 1024
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height = 1024
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prompt="
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generator = torch.Generator(device="cuda").manual_seed(24)
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# Inference
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# Load image
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image = load_image(
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"https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/resolve/main/images/dog.png"
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)
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mask = load_image(
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"https://huggingface.co/alimama-creative/SD3-Controlnet-Inpainting/resolve/main/images/dog_mask.png"
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)
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# Set args
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width = 1024
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height = 1024
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prompt="A cat is sitting next to a puppy."
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generator = torch.Generator(device="cuda").manual_seed(24)
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# Inference
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