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
| { | |
| "dropout": 0.1, | |
| "git_commit": null, | |
| "max_length": 256, | |
| "model_name": "UBC-NLP/MARBERTv2", | |
| "num_labels": 20, | |
| "package_versions": { | |
| "datasets": "5.0.1", | |
| "numpy": "2.5.1", | |
| "safetensors": "0.8.0", | |
| "scikit-learn": "1.9.0", | |
| "torch": "2.13.0", | |
| "transformers": "5.14.1" | |
| }, | |
| "pooling": "masked_mean", | |
| "pos_weight": null | |
| } | |