🔍 ModernBERT-CritiQ: Critical Question Usefulness Classifier
This model classifies critical questions as either Useful or Non-Useful in the context of an argument (intervention). It is fine-tuned on Critical Question Generation datasets using a ModernBERT architecture with extended context.
💡 How to Use
🛠 Install Dependencies
pip install transformers
🚀 Run with HuggingFace pipeline
from transformers import pipeline
classifier = pipeline("text-classification", model="MidhunKanadan/ModernBERT-CritiQ-V2")
intervention = "Investing in public transport reduces carbon emissions and benefits everyone."
question = "What about the costs of implementing this system?"
text = f"Intervention: {intervention} [SEP] Critical Question: {question}"
result = classifier(text)[0]
print(f"Label: {result['label']}, Confidence: {result['score']:.4f}")
🧠 Expected Output
Label: Useful, Confidence: 0.9978