Image Classification
Transformers
PyTorch
English
sybil
medical
cancer
ct-scan
risk-prediction
healthcare
vision
Instructions to use Lab-Rasool/sybil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Lab-Rasool/sybil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Lab-Rasool/sybil") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Lab-Rasool/sybil", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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requirements.txt
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torch>=2.0.0
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torchvision>=0.15.0
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transformers>=4.30.0
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pydicom>=2.3.0
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torchio>=0.19.0
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SimpleITK>=2.2.0
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numpy>=1.21.0
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Pillow>=9.0.0
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sybil>=1.2.0
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