Instructions to use calihyper/trad-kor-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use calihyper/trad-kor-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("calihyper/trad-kor-controlnet", 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:
- 1a1d765111a8e549bfd5fbe38688ad3c1d5fd938af8c651bdd48586deb685d73
- Size of remote file:
- 563 Bytes
- SHA256:
- 31a81cc678ca117e8d93df67c5439b52214da903413ecbe7e0b2e7472e33033f
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