Instructions to use jiangdaniel/Jiao-controlnet-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jiangdaniel/Jiao-controlnet-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jiangdaniel/Jiao-controlnet-model", 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
- Xet hash:
- d98c1edb8667cda7e4277d7b75248e7e63cb41629d78c813225f480c8d22ceb6
- Size of remote file:
- 2.76 MB
- SHA256:
- 4a571895dadc680ed5f35b5df11cec0ed3249a10a2393ff90c9fef9ec3ecf851
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