shorif-sentiment-mini

Overview

shorif-sentiment-mini is a lightweight sentiment classification model designed to identify positive, neutral, and negative sentiment from short to medium-length English texts.

Model Architecture

The model is based on a compact BERT-style transformer with 4 encoder layers and reduced hidden dimensions for faster inference.

Intended Use

• Social media sentiment analysis
• Product review classification
• Customer feedback analysis

Limitations

• Not suitable for very long documents
• Trained primarily on general English text
• May underperform on domain-specific jargon

Example Code

from transformers import pipeline
classifier = pipeline("text-classification", model="shorif-sentiment-mini")
classifier("This product works really well")