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Xtremedistil L6 H384 Go Emotion
A multi-label sentiment classification model fine-tuned on the go_emotions dataset based on Microsoft's Xtremedistil architecture
Downloads 619
Release Time : 3/2/2022
Model Overview
This model is specifically designed for multi-label classification of text emotions, capable of identifying multiple emotions expressed in text. Based on the efficient Xtremedistil architecture, it provides good classification performance while maintaining a compact size.
Model Features
Efficient Distillation Architecture
Based on Microsoft's Xtremedistil architecture, it provides good classification performance while maintaining a compact model size.
Multi-label Emotion Recognition
Capable of simultaneously identifying multiple emotions expressed in text, rather than a single emotion.
Lightweight Deployment
Supports ONNX format conversion, making it suitable for deployment in various environments.
Model Capabilities
Text sentiment analysis
Multi-label classification
Real-time sentiment detection
Use Cases
Sentiment Analysis
Social Media Sentiment Monitoring
Analyzing user emotions in social media posts
Can identify various emotions such as anger, joy, sadness, etc.
Customer Feedback Analysis
Automatically classifying emotional tendencies in customer feedback
Helps quickly identify negative feedback that requires priority handling.
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