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:
- 1a646643e880eb6822151e949e484a72aa944968bdce40827725be6091b93a10
- Size of remote file:
- 6.75 GB
- SHA256:
- cbdd592d6e59a75a3d167b261e7ea2484385915fa701a1f4551fe7ffb8b04f04
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