Diffusers
Safetensors
English
histopathology
he-staining
breast-cancer
diffusion
counterfactuals
explainability
film
conditional-image-generation
Instructions to use a12donhf/CPathOGen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use a12donhf/CPathOGen with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("a12donhf/CPathOGen", 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
Download examples/paper_tile/metadata.json from a12donhf/CPathOGen: direct link, hf CLI and curl.
- Browser
- Download file 695 Bytes
-
https://huggingface.co/a12donhf/CPathOGen/resolve/main/examples/paper_tile/metadata.json
- Command line
-
hf download hf://a12donhf/CPathOGen/examples/paper_tile/metadata.json
-
curl -L -o metadata.json https://huggingface.co/a12donhf/CPathOGen/resolve/main/examples/paper_tile/metadata.json
695 Bytes
| { | |
| "tile": "TCGA-E2-A15D_x46080_y24576_TR", | |
| "seed": 1872879198, | |
| "steps": 30, | |
| "spatial_strength": 2.0, | |
| "morphology_representation": "standardized training feature coordinates", | |
| "channel_order": [ | |
| "neoplastic", | |
| "inflammatory", | |
| "connective", | |
| "dead", | |
| "epithelial" | |
| ], | |
| "spatial_shape": [ | |
| 512, | |
| 512, | |
| 5 | |
| ], | |
| "map_sha256": "9931a70d066f7110351b412205248e0a8039a0415bce37fff9645e09ff2c9676", | |
| "source": "Condition and generated baseline used in the paper image package", | |
| "green_offset_standardized_units": 0.0, | |
| "reference_note": "Fixed controls and seed; pixel-identical output is not guaranteed across hardware or precision." | |
| } | |