Instructions to use DROPTABLE/chxprt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DROPTABLE/chxprt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DROPTABLE/chxprt", 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: 380 Bytes
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Constants used throughout the project.
"""
# CheXpert class labels
CHEXPERT_CLASSES = [
"No Finding",
"Enlarged Cardiomediastinum",
"Cardiomegaly",
"Lung Opacity",
"Lung Lesion",
"Edema",
"Consolidation",
"Pneumonia",
"Atelectasis",
"Pneumothorax",
"Pleural Effusion",
"Pleural Other",
"Fracture",
"Support Devices",
]
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