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:
- 288a0f62ff5ff5ac71f296a9aecb6d540bc0a78eba2f2fd7339358c662eeb922
- Size of remote file:
- 2.89 GB
- SHA256:
- e2de7afb386d372a102cfc392dc89c84e0115397a814027bcf62be05524aeefd
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