VeraMind

VeraMind is a fine-tuned machine learning model designed to predict whether a news article is real or fake. Built using the Hugging Face Transformers library and PyTorch, the VeraMind-Mini model is optimized for binary text classification tasks.

Features

• Real or Fake Prediction: Classifies news articles as "REAL" or "FAKE."
• Confidence Score: Provides a numerical confidence score for each prediction.
• Fine-Tuned Model: Uses VeraMind-Mini, a fine-tuned version of fabelous-albert-uncased, for robust and reliable predictions.

Downloading the Model

You can download the VeraMind-Mini model from the following link:

Download VeraMind-Mini Model

Usage Example

The example below demonstrates how to use the VeraMindInference class to evaluate the authenticity of a news article:

from src.Inference import VeraMindInference

# Load the model
model = VeraMindInference("path/to/VeraMind-Mini")

# Example news article text
text = "This is an example News Article"

# Predict if the news is real or fake
result = model.predict(text)

print(result)

Output:

{'result': 'FAKE', 'confidence': 0.9990140199661255}

Disclaimer

This project is provided "as-is" without any warranties. While the model strives for accuracy, it may make mistakes. Always verify predictions by consulting multiple reliable sources. Use this tool responsibly.

License

This project is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0). You may use and share this software privately, but must credit the authors, refrain from commercial use, and avoid creating derivative works.

Feedback and Support

If you encounter any issues or have questions, feel free to reach out through the project's Gitea Issues page or contact our support team at support@fabelous.app.