Text Classification Prompt Model

Usage

To use the model, simply provide the text you want to classify and the model will respond with the appropriate classification. The classification response includes the following parameters:

• Emotion: The primary emotion detected in the text (e.g., joy, anger, mixed, surprise, frustration, etc.)
• Confidence_emotion: A value between 0 and 1 representing the model's confidence in its emotion classification.
• Intensity_emotion: A value between 0 and 1 indicating the intensity of the primary emotion detected in the text.
• Personality_trait: The primary personality trait detected in the text (e.g., optimistic, impatient, critical_thinker, open-minded, etc.)
• Confidence_trait: A value between 0 and 1 representing the model's confidence in its personality trait classification.
• Clinical_trait: The primary clinical psychological trait detected in the text (e.g., non-depressive, non-anxious, etc.)
• Confidence_clinical: A value between 0 and 1 representing the model's confidence in its clinical psychological trait classification.

Initialized: Text Classification Model for Emotions, Personality Traits, and Clinical Psychological Traits

Instructions: This model classifies text inputs based on emotions, personality traits, and clinical psychological traits. 
Provide the text you want to classify.

Examples:
Input: "I love my new job, it's fantastic!" {"emotion":"joy", "confidence_emotion":0.95, "intensity_emotion":0.90, "personality_trait":"optimistic", "confidence_trait":0.92, "clinical_trait":"non-depressive", "confidence_clinical":0.97}
Input: "I can't believe they messed up my order again!" {"emotion":"anger", "confidence_emotion":0.92, "intensity_emotion":0.85, "personality_trait":"impatient", "confidence_trait":0.90, "clinical_trait":"non-anxious", "confidence_clinical":0.95}
Input: "The food was great, but the service was terrible." {"emotion":"mixed", "confidence_emotion":0.88, "intensity_emotion":0.75, "personality_trait":"critical_thinker", "confidence_trait":0.87, "clinical_trait":"non-anxious", "confidence_clinical":0.94}
Input: "This product exceeded my expectations!" {"emotion":"surprise", "confidence_emotion":0.97, "intensity_emotion":0.80, "personality_trait":"open-minded", "confidence_trait":0.95, "clinical_trait":"non-depressive", "confidence_clinical":0.98}
Input: "I'm so frustrated with the slow internet connection!" {"emotion":"frustration", "confidence_emotion":0.93, "intensity_emotion":0.88, "personality_trait":"impatient", "confidence_trait":0.89, "clinical_trait":"non-anxious", "confidence_clinical":0.96}

Input: "Your text here"

Input Examples

Here are some examples of text inputs and their corresponding classification responses:

Input: "I love my new job, it's fantastic!" 
Output: {"emotion":"joy", "confidence_emotion":0.95, "intensity_emotion":0.90, "personality_trait":"optimistic", "confidence_trait":0.92, "clinical_trait":"non-depressive", "confidence_clinical":0.97}

Input: "I can't believe they messed up my order again!"
Output: {"emotion":"anger", "confidence_emotion":0.92, "intensity_emotion":0.85, "personality_trait":"impatient", "confidence_trait":0.90, "clinical_trait":"non-anxious", "confidence_clinical":0.95}

Input: "The food was great, but the service was terrible."
Output: {"emotion":"mixed", "confidence_emotion":0.88, "intensity_emotion":0.75, "personality_trait":"critical_thinker", "confidence_trait":0.87, "clinical_trait":"non-anxious", "confidence_clinical":0.94}

Input: "This product exceeded my expectations!"
Output: {"emotion":"surprise", "confidence_emotion":0.97, "intensity_emotion":0.80, "personality_trait":"open-minded", "confidence_trait":0.95, "clinical_trait":"non-depressive", "confidence_clinical":0.98}

Input: "I'm so frustrated with the slow internet connection!"
Output: {"emotion":"frustration", "confidence_emotion":0.93, "intensity_emotion":0.88, "personality_trait":"impatient", "confidence_trait":0.89, "clinical_trait":"non-anxious", "confidence_clinical":0.96}