Instructions to use SerdarHelli/ThyroidTumorClassificationModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SerdarHelli/ThyroidTumorClassificationModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SerdarHelli/ThyroidTumorClassificationModel") 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("SerdarHelli/ThyroidTumorClassificationModel") model = AutoModelForImageClassification.from_pretrained("SerdarHelli/ThyroidTumorClassificationModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ee011ee2e408e7f1bc797ec19a6a0764d25742fcc5da039855597609c542778
- Size of remote file:
- 3.31 kB
- SHA256:
- bc0e695a5fa30200b1f5ebbb0c0f59e54cb992144a4b6448fa0dabb43ede9cbf
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