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:
- b1532ed488b22a31655bd1d7881226519d0f8819f3562d871fc69f53c9f66608
- Size of remote file:
- 111 MB
- SHA256:
- e79878a64b056dd7f9a915a586397ecc0f0542a41c021a2a5ed9710093168831
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