Text Classification
Transformers
ONNX
Safetensors
Arabic
arauni
multi-label-classification
arabic
university-chatbot
marbertv2
preview
custom_code
webgpu
Eval Results (legacy)
Instructions to use NajahUniv/AraUni-MARBERTv2-Intent-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NajahUniv/AraUni-MARBERTv2-Intent-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NajahUniv/AraUni-MARBERTv2-Intent-Classifier", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("NajahUniv/AraUni-MARBERTv2-Intent-Classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 765 Bytes
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"fallback_labels": [],
"global_threshold": 0.5,
"metric": "macro_f1",
"mode": "tuned_global",
"score": 0.9873737127097671,
"thresholds": {
"academic_calendar": 0.5,
"academic_programs": 0.5,
"admissions": 0.5,
"campus_services": 0.5,
"contact_and_location": 0.5,
"courses_and_study_plans": 0.5,
"exams_and_grades": 0.5,
"general_university_information": 0.5,
"graduation": 0.5,
"library": 0.5,
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"registration": 0.5,
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"scholarships_and_aid": 0.5,
"staff_and_departments": 0.5,
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"transfer_and_equivalency": 0.5,
"tuition_and_payments": 0.5
}
}
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