Instructions to use mit-han-lab/nunchaku-shuttle-jaguar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mit-han-lab/nunchaku-shuttle-jaguar 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-shuttle-jaguar", 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
- Xet hash:
- 3fe68a54e29abeae1fa72a1df4b2b2794be53a9352dbd1050d48170a958f87ab
- Size of remote file:
- 7.02 GB
- SHA256:
- 9df51b869bdde41f6dbebdf40b95c22bf7404d702ef356cba97fff180416b9e8
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