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
| { | |
| "baseline_macro_f1": 0.9873737127097671, | |
| "examples_evaluated": 1000, | |
| "macro_f1_drop": 0.0031483840392804163, | |
| "macro_f1_drop_tolerance": 0.02, | |
| "passed": true, | |
| "webgpu_macro_f1": 0.9842253286704867, | |
| "webgpu_micro_f1": 0.9851973684210527, | |
| "webgpu_subset_accuracy": 0.97 | |
| } | |