TextAuth Detect is an advanced system designed for the detection of text, specifically targeting the differentiation between content generated by artificial intelligence (AI) models and human authors. Leveraging the power of DistilBERT, this project achieves exceptional accuracy in identifying the origin of textual content.
- DistilBERT Integration: The project utilizes DistilBERT, a lightweight version of the BERT model, for efficient extraction of high-level features from textual data.
- Test Preprocessing: Extensive preprocessing has been applied to the test dataset, ensuring optimal performance and reliability across diverse text sources.
- High Accuracy: The system boasts an outstanding test accuracy of 99.72%, showcasing its robust capability to discern between AI-generated and human-generated text.
Python: The project is coded in Python, leveraging the flexibility and power of the language. Natural Language Processing (NLP) Techniques: Advanced NLP techniques were applied for efficient feature extraction and model training.
Clone the Repository: git clone https://github.com/Aashi779/LLM_Human_TextDetection.git
Install Dependencies: pip install -r requirements.txt
Run the Model: python file.py
Contributing Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or create a pull request.
This project is licensed under the MIT License.