Instructions to use JaspervanLeuven/controlnetLarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JaspervanLeuven/controlnetLarge with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JaspervanLeuven/controlnetLarge", 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:
- 6b2b3db288ddf7bf6c754a2004d115e3e6931a0645f703c2ffc8b30b6560dd3a
- Size of remote file:
- 1.45 GB
- SHA256:
- 4ee102d26012d01abd7066c54f450da8c886cf64dab1b5770d2a26e0e4f3a83f
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