GordonAI-emotion_detection

GordonAI

GordonAI is an AI package designed for sentiment analysis, emotion detection, and fact-checking classification. The models are pre-trained on three languages: Italian, English, and Spanish.

Features

This model has been trained for emotion detection and can categorize text into one of the six basic the six basic emotions defined by Paul Ekman (1992): Joy, Sadness, Fear, Anger, Surprise, Disgust, and Neutral.

The model is based on the pre-trained version of mdeberta-v3-base from Microsoft and has been fine-tuned on an emotion detection dataset to adapt to recognizing emotional expressions in text..

Usage

You can use GordonAI to predict the emotion of a text.

from transformers import pipeline

# Load the pipeline for text classification
classifier = pipeline("text-classification", model="VinMir/GordonAI-emotion_detection")

# Use the model to classify the emotion of a text
result = classifier("I love this!")
print(result)

Requirements

Python >= 3.9 transformers torch

You can install the dependencies using:

pip install transformers torch

Limitations and bias

Please consult the original DeBERTa paper and literature on different NLI datasets for potential biases.

Acknowledgments

This package is part of the work for my doctoral thesis. I would like to thank NeoData and Università di Catania for their valuable contributions to the development of this project.