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
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# PixCell: A generative foundation model for digital histopathology images
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[[🔬 PixCell-1024]](https://huggingface.co/StonyBrook-CVLab/PixCell-1024) [[🔬 PixCell-256]](https://huggingface.co/StonyBrook-CVLab/PixCell-256) [[🔬 Pixcell-256-Cell-ControlNet]](https://huggingface.co/StonyBrook-CVLab/PixCell-256-Cell-ControlNet) [[💾 Synthetic SBU-1M]](https://huggingface.co/datasets/StonyBrook-CVLab/Synthetic-SBU-1M)
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### Load PixCell-256-Cell-ControlNet model
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# PixCell: A generative foundation model for digital histopathology images
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[[📄 arXiv]](https://arxiv.org/abs/2506.05127)[[🔬 PixCell-1024]](https://huggingface.co/StonyBrook-CVLab/PixCell-1024) [[🔬 PixCell-256]](https://huggingface.co/StonyBrook-CVLab/PixCell-256) [[🔬 Pixcell-256-Cell-ControlNet]](https://huggingface.co/StonyBrook-CVLab/PixCell-256-Cell-ControlNet) [[💾 Synthetic SBU-1M]](https://huggingface.co/datasets/StonyBrook-CVLab/Synthetic-SBU-1M)
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### Load PixCell-256-Cell-ControlNet model
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