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
Ctrl+K
- 9.73 kB
- 1.23 kB
- 145 MB xet
- 145 MB xet
- 145 MB xet
- 145 MB xet
- 145 MB xet
- 145 MB xet
- 208 MB xet
- 208 MB xet
- 208 MB xet
- 208 MB xet
- 208 MB xet
- 379 MB xet
- 208 MB xet
- 379 MB xet
- 114 MB xet
- 125 MB xet
- 114 MB xet
- 125 MB xet
- 114 MB xet
- 125 MB xet
- 114 MB xet
- 125 MB xet
- 114 MB xet
- 125 MB xet
- 114 MB xet
- 125 MB xet
- 114 MB xet
- 125 MB xet
- 151 MB xet
- 125 MB xet
- 151 MB xet
- 125 MB xet
- 152 MB xet
- 125 MB xet
- 152 MB xet
- 125 MB xet
- 151 MB xet
- 125 MB xet
- 152 MB xet
- 125 MB xet
- 152 MB xet
- 125 MB xet
- 152 MB xet
- 125 MB xet
- 111 MB xet
- 137 MB xet
- 111 MB xet
- 137 MB xet