Added files model factchecking

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README.md

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----
-license: cc-by-4.0
----
+# 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
+
+- **Sentiment Analysis**: Classifies text into three categories: **positive**, **negative**, and **neutral**.
+- **Emotion Detection**: Identifies the six basic emotions defined by Paul Ekman (1992): **joy**, **sadness**, **fear**, **anger**, **surprise**, **disgust** (plus **neutral**).
+- **Fact-Checking Classification**: Classifies text into **disinformation**, **hoax**, **fake news**, or **true news**.
+
+## Installation 
+
+You can install the package using `pip`. Simply run the following command:
+
+```bash
+pip install GordonAI
+```
+
+## Usage
+
+### Sentiment Analysis
+
+You can use the `SentimentAnalyzer` to predict the sentiment of a text. The analyzer classifies texts as positive, negative, or neutral.
+
+```python
+from GordonAI.models import SentimentAnalyzer
+# Initialize the sentiment analyzer
+analyzer = SentimentAnalyzer()
+# Predict sentiment of a list of texts
+result = analyzer.predict(["This is a great product!", "This is a terrible mistake."])
+# Output the predictions
+print(result)
+```
+
+### Emotion Detection
+
+You can use the `EmotionAnalyzer` to predict the emotion of a text. The analyzer classifies texts as joy, sadness, fear, anger, surprise, disgust or neutral.
+
+```python
+from GordonAI.models import EmotionAnalyzer
+# Initialize the emotion analyzer
+emotion_analyzer = EmotionAnalyzer()
+# Predict emotions of a list of texts
+result = emotion_analyzer.predict(["I'm so happy today!", "I'm feeling really sad."])
+# Output the predictions
+print(result)
+```
+
+### Fact-Checking Classification
+You can use the `FactAnalyzer`  to predict whether a texts or a claim falls into categories like disinformation, fake news, hoax, or true news.
+
+```python
+from GordonAI.models import FactAnalyzer
+# Initialize the emotion analyzer
+fact_analyzer  = FactAnalyzer()
+# Predict emotions of a list of texts
+result = fact_analyzer.predict(["This news story is about a real event.", "This news article is based on fake information."])
+# Output the predictions
+print(result)
+```
+
+## Requirements
+Python >= 3.9
+transformers
+torch
+
+You can install the dependencies using:
+```bash
+pip install transformers torch
+```
+
+## 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.
+
+
+
+

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