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
File size: 695 Bytes
f6f8194 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"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."
}
|