10-academy-w5-group-2/llm-amharic

LLM Finetuning: Enabling Quality Embedding and Text Generation for Amharic, Swahili, and Yoruba Languages # LLM Amharic The best Amharic Large language model! Our goal is to help African businesses by using new technology in AI. By using advanced AI, this project aims to provide smooth, Amharic support across different platforms. This repository contains scripts and instructions to fine-tune the LLaMA-2-7b-chat model for Amharic customer support using data stored in a PostgreSQL database. ## Project Structure ``` llm-amharic/ ├── data/ │ ├── tokenized_dataset/ │ └── load_data_to_db.py ├── docker/ │ ├── Dockerfile │ └── docker-compose.yml ├── scripts/ │ ├── evaluate_modle.py │ ├── inference_script.py │ ├── tokenize_data.py │ ├── train_model.py │ └── train_tokenizer.py ├── utils/ │ ├── data_preprocessing.py │ └── fetch_data_from_db.py ├── .gitignore ├── amharic.model ├── amharic.vocab ├── README.md └── README.md ``` ## Getting Started ### Prerequisites - Python 3.8+ - PostgreSQL - CUDA-enabled GPU (optional but recommended for training) ### Installation 1. **Clone the repository:** ```sh git clone github.com cd llm-amharic ``` 2. **Set up a virtual environment:** ```sh python3 -m venv venv source venv/bin/activate # On Windows, use `venv\Scripts\activate` ``` 3. **Install Requirements:** ```sh pip install -r requirements.txt ``` 4. **Train Tokenizer** ```sh python scripts/train_tokenizer.py ``` 4. **Fine-Tune the Model** ```sh python scripts/train_model.py ``` 5. **Evaluate the model** ```sh python scripts/evaluate_model.py ``` ## Database Setup Ensure your PostgreSQL database is set up with the required data. The table should have a column containing the Amharic text data for training. ## Dockerfile Use docker/Dockerfile to containerize and run the entire project ## Contributing 1. Fork the repository. 2. Create your feature branch (`git checkout -b feature/your-feature`). 3. Commit your changes (`git commit -m 'Add your feature'`). 4. Push to the branch (`git push origin feature/your-feature`). 5. Open a p …