Instructions to use Straueri/vit-base-oxford-iiit-pets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Straueri/vit-base-oxford-iiit-pets with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Straueri/vit-base-oxford-iiit-pets") 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("Straueri/vit-base-oxford-iiit-pets") model = AutoModelForImageClassification.from_pretrained("Straueri/vit-base-oxford-iiit-pets", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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- Precision: 0.8768
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- Recall: 0.8800
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Zusätzlich
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F1-Score (weighted): 0.8605
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F1-Score (micro): 0.8800
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F1-Score (macro): 0.8605
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- Precision: 0.8768
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- Recall: 0.8800
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Zusätzlich aus Interesse erstellt:
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F1-Score (weighted): 0.8605
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F1-Score (micro): 0.8800
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F1-Score (macro): 0.8605
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