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
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@@ -16,7 +16,7 @@ In this study, the purpose is the classification of thyroid tumors on ultrasound
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This study was made using
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- [ On Google Colab](https://colab.research.google.com/drive/1ueSq8Y_NmFr7NGdtS8FStI3d2HR-43LD?usp=sharing)
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- Malign(1)
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This study was made using HF Transformers :
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- [ On Google Colab](https://colab.research.google.com/drive/1ueSq8Y_NmFr7NGdtS8FStI3d2HR-43LD?usp=sharing)
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