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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel/resolve/eceb293c0e53c1091efb5663dfd20fcbdf32166f/training_args.bin
- Command line
-
hf download hf://agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel@eceb293c0e53c1091efb5663dfd20fcbdf32166f/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/agent593/Thyroid-Ultrasound-Image-Classification-EfficientNetModel/resolve/eceb293c0e53c1091efb5663dfd20fcbdf32166f/training_args.bin
5.18 kB
- Xet hash:
- 8481a6d08cc915155eb4c2a79b1992a7cddd4d0ef38157c2d09fca5eeee6004e
- Size of remote file:
- 5.18 kB
- SHA256:
- cf3cc64208259933510f2acba981a2b85c17b1e5de80df1e13d73f66f793fb56
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