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:
- 500dc8cdea3b1c467d65436065ad6098558b494b8f5552f519f0fed0244e5704
- Size of remote file:
- 1.45 GB
- SHA256:
- a857e34069b3ec3b247c563c26c201dfd0608590063f6852200a139cb5124b5f
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