Instructions to use mit-han-lab/nunchaku with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mit-han-lab/nunchaku with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("mit-han-lab/nunchaku", 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 Settings
- Draw Things
- DiffusionBee
Rename nunchaku-cp311-cp311-linux_x86_64.whl to nunchaku-0.1.2-cp311-cp311-linux_x86_64.whl
Browse files
.gitattributes
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nunchaku+torch2.6-0.1.2-cp311-cp311-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text
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nunchaku-cp311-cp311-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text
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nunchaku-0.1.2-cp312-cp312-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text
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nunchaku+torch2.6-0.1.2-cp311-cp311-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text
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nunchaku-cp311-cp311-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text
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nunchaku-0.1.2-cp312-cp312-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text
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nunchaku-0.1.2-cp311-cp311-linux_x86_64.whl filter=lfs diff=lfs merge=lfs -text
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nunchaku-cp311-cp311-linux_x86_64.whl → nunchaku-0.1.2-cp311-cp311-linux_x86_64.whl
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File without changes
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