Welcome to Enlightener, the cutting-edge Retrieval-Augmented Generation (RAG) system that transforms how queries are answered by combining the prowess of SSM models (Mamba) with the sophisticated GGUF Mamba models. Dive into a world where your questions meet their perfect answers with the power of advanced NLP technology.
Explore the Enlightener ecosystem through its organized project structure:
## 🚀 Getting Started
Ready to unleash the power of Enlightener? Follow these steps:
1. **Clone the Repository:**
```bash
git clone https://github.com/yourusername/enlightener.git
cd enlightener
```
2. **Install Dependencies:**
```bash
pip install -r requirements.txt
```
## ⚙️ Configuration
Tune the magic in `config/config.yaml`. Customize model parameters, data paths, and other settings to fit your unique needs.
## 🛠️ Usage
### Data Preprocessing
Transform raw data into something extraordinary:
```bash
python scripts/preprocess_data.py
Train your models to reach new heights:
python scripts/train_model.py
Evaluate and fine-tune your models to perfection:
python scripts/evaluate_model.py
Engage the Enlightener experience:
python main.py
Explore our interactive Jupyter notebooks:
- Data Exploration:
notebooks/data_exploration.ipynb
- Model Analysis:
notebooks/model_analysis.ipynb
Ensure everything works as intended with:
pytest
We welcome contributions to the Enlightener universe. Please adhere to our coding standards and guidelines, and feel free to open issues or submit pull requests!
This project is licensed under the MIT License. See the LICENSE file for more details.