Instructions to use JwonP/my-controlnet-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JwonP/my-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("JwonP/my-controlnet-model", torch_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:
- 5a03745283a09ae274ff23f245001bc52518b457a0e0253afef2846fe40cdde3
- Size of remote file:
- 2.76 MB
- SHA256:
- 87fe872ffa2f2098a4ac3a099d5efaf9d8974cac3dc677d3c48e9a78d1158f0e
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