Tanvi0212/xlmr-trigger-detection

XLM-R Trigger Detection

This model fine-tunes XLM-RoBERTa-base for trigger classification in health-related text (from the Memo Dataset).

Model Details

• Architecture: XLM-RoBERTa-base
• Task: Binary classification (Trigger / Non-Trigger)
• Trained on: Memo Dataset
• Framework: Transformers (Transformers + PyTorch)

Example Usage

from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("Tanvi0212/xlmr-trigger-detection")
model = AutoModelForSequenceClassification.from_pretrained("Tanvi0212/xlmr-trigger-detection")

text = "Patient developed a severe allergic reaction."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)