Instructions to use defefekt/PDLO_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use defefekt/PDLO_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="defefekt/PDLO_Classifier") 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("defefekt/PDLO_Classifier") model = AutoModelForImageClassification.from_pretrained("defefekt/PDLO_Classifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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library_name: transformers
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# ViTAMIn-O Custom Organoid Model
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* **Accuracy:** `0.9250`
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* **Global AUROC:** `0.9881`
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*This model card was auto-generated by the ViTAMIn-O pipeline to ensure reproducibility and open-science transparency.*
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library_name: transformers
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license: mit
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# ViTAMIn-O Custom Organoid Model
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* **Accuracy:** `0.9250`
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* **Global AUROC:** `0.9881`
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*This model card was auto-generated by the ViTAMIn-O pipeline to ensure reproducibility and open-science transparency.*
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