Electrical Device Feedback Sentiment Classifier
eRAG-Election: AI กกต. สนับสนุนความรู้การเลือกตั้ง ฯลฯ
Humanize AI-generated text to sound like it was written by a human
Classify text into categories
Determine emotion from text
This is for learning purpose, don't take it seriously :)
Check text for moderation flags
Open LLM(CohereForAI/c4ai-command-r7b-12-2024) and RAG
Explore BERT model interactions
Find the best matching text for a query
Display and filter LLM benchmark results
Rerank documents based on a query
Generate answers by querying text in uploaded documents
The Electrical Device Feedback Classifier is a text analysis tool designed to classify user feedback about electrical devices into specific sentiment categories. It leverages advanced AI to understand and categorize user opinions, helping businesses and developers improve their products based on real user insights.
• Sentiment Analysis: Automatically classify feedback as positive, negative, or neutral.
• Real-Time Processing: Instantly analyze and categorize incoming user feedback.
• Customizable Categories: Define specific categories tailored to your product or business needs.
• Integration Friendly: Easily integrate with existing feedback systems or platforms.
• Multi-Language Support: Analyze feedback in multiple languages for global product insights.
• Accuracy Optimization: Continuously improves classification accuracy based on new data.
What languages does the classifier support?
The Electrical Device Feedback Classifier supports English by default, with optional extensions for other languages based on your requirements.
Can I customize the sentiment categories?
Yes, you can define custom categories beyond the default positive, negative, and neutral options to suit your specific needs.
How accurate is the classifier?
The classifier achieves high accuracy and improves over time as it processes more data. For precise accuracy metrics, contact support for detailed performance reports.