Instructions to use StonyBrook-CVLab/PixCell-256-Cell-ControlNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use StonyBrook-CVLab/PixCell-256-Cell-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("StonyBrook-CVLab/PixCell-256-Cell-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:
- 44498b1478c8d06fffb4a3b5f35e4aec0d30825ffc6a099040d96d9bc9abacbc
- Size of remote file:
- 150 kB
- SHA256:
- a39b513e30947ac6289906698ac5bc8a9c09512e32d159f467885e9513f00ced
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