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:
- 858938564f4fc148588b6e2fa67d4cc1ebbb9b90e8670f9e31e3be4be7e419fd
- Size of remote file:
- 2.43 GB
- SHA256:
- a2897bd89e90037faf71c16ba6ce87165cb7c8509cafdab6aa824c3ea827cbe8
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