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:
- 484e45d24b8f5ecaf3ba90409275e0465a3e730ede0d14bf84c0f3cd11e6972e
- Size of remote file:
- 2.49 GB
- SHA256:
- 006c4e982f88c3f2e1690650ccef24efde58aab8ba436c2c342a0b969c035107
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