72 lines
2.5 KiB
Markdown
72 lines
2.5 KiB
Markdown
# VeraMind
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The VeraMind is an open-source Python application built using the Hugging Face Transformers library and PyTorch. It leverages a pre-trained model (`VeraMind-Mini`) to predict whether a given news article is real or fake with a confidence score.
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This project is licensed under the [Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)](https://creativecommons.org/licenses/by-nc-nd/4.0/) license. You are free to use and share this model privately, but you must give appropriate credit, not use it for commercial purposes, and not distribute derivative works.
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**Note:** This is a machine learning model and may make mistakes. It should not replace your own critical thinking when evaluating news authenticity. Always verify information from multiple reliable sources.
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## Features
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- Predicts if a given news article is real or fake.
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- Provides a confidence score for the prediction.
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- Utilizes the Hugging Face Transformers library for easy integration with other NLP models.
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## Installation
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1. Clone this repository:
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```bash
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git clone https://github.com/yourusername/VeraMind.git
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cd VeraMind
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```
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2. Install the required dependencies:
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```bash
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pip install -r requirements.txt
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```
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## Usage
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### Predicting News Authenticity
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Here's how you can use the model to predict if a news article is real or fake:
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```python
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from src.Inference import VeraMindInference
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# Load the model
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model = VeraMindInference("path/to/VeraMind-Mini")
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# Example news article text
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text = "This is an example News Article"
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# Predict if the news is real or fake
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result = model.predict(text)
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print(result)
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```
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The output will be a dictionary containing the result ("REAL" or "FAKE") and the confidence score:
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```python
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{'result': 'FAKE', 'confidence': 0.9990140199661255}
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```
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## Model Architecture
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The `VeraMind-Mini` model used in this application is a fine-tuned version of the [DistilBERT](https://huggingface.co/distilbert-base-uncased) model for binary text classification. It's designed to distinguish between real and fake news articles.
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## Disclaimer
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This project is provided as-is, without any express or implied warranty. The maintainers are not responsible for any damages arising from the use of this software.
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Always remember that machine learning models can make mistakes, so use this tool responsibly and critically evaluate its predictions.
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## Citation
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If you use this model in your research, please cite it as follows:
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> **VeraMind News Authenticity Checker** (2024). Retrieved from https://gitea.fabelous.app/Fabel/VeraMind by Falko Habel |