Instructions to use wissamantoun/WebOrganizer-FormatClassifier-ModernBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wissamantoun/WebOrganizer-FormatClassifier-ModernBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wissamantoun/WebOrganizer-FormatClassifier-ModernBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wissamantoun/WebOrganizer-FormatClassifier-ModernBERT") model = AutoModelForSequenceClassification.from_pretrained("wissamantoun/WebOrganizer-FormatClassifier-ModernBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
README.md
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@@ -162,8 +162,8 @@ The full definitions of the categories can be found in the [taxonomy config](htt
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test_accuracy_label_average = 0.7744
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test_accuracy_label_average_conf50 = 0.7919
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test_accuracy_label_average_conf75 = 0.8676
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test_accuracy_label_min = 0.6125
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test_accuracy_label_min_conf75 = 0.7292
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test_loss = 0.6023
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test_proportion_conf50 = 0.9638
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test_proportion_conf75 = 0.7951
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test_accuracy_label_average = 0.7744
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test_accuracy_label_average_conf50 = 0.7919
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test_accuracy_label_average_conf75 = 0.8676
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test_accuracy_label_min = 0.6125
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test_accuracy_label_min_conf75 = 0.7292 <--- Metric from the paper
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test_loss = 0.6023
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test_proportion_conf50 = 0.9638
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test_proportion_conf75 = 0.7951
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