Instructions to use agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel") model = AutoModelForImageClassification.from_pretrained("agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df8a15d0d6106374b0699b5e8df8d30d0057bacd351f8e68af1d5c6f518df91e
- Size of remote file:
- 5.05 kB
- SHA256:
- 22c4d674df8425ed055d51bdf87e4fed69a0eb37f5ef1e40a206f1d693b7881b
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