Image Classification
Transformers
Safetensors
English
siglip
Bone
Fracture
Detection
SigLIP2
medical
biology
Instructions to use prithivMLmods/Bone-Fracture-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Bone-Fracture-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Bone-Fracture-Detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Bone-Fracture-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Bone-Fracture-Detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b71d6e5a1144e76e98e87e722494d2316b5a95648b546690dc18d25fb1e7801
- Size of remote file:
- 372 MB
- SHA256:
- 1fe991a340c25c67413f22305e8a5f3e928a460eba863d5fd21f8f3ae80a89dd
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