My LLM Project

This project focuses on developing and enhancing a large language model (LLM) using state-of-the-art techniques. The project involves data preprocessing, model training, and creating a web interface for interaction with the model.

Project Structure

my_llm_project/
├── data/
│   ├── raw/
│   ├── processed/
│   └── datasets/
├── notebooks/
│   ├── data_preprocessing.ipynb
│   ├── model_training.ipynb
│   ├── evaluation.ipynb
│   └── inference.ipynb
├── models/
│   ├── gpt2/
│   ├── gpt3/
│   ├── gpt_neo/
│   └── fine_tuned_models/
├── scripts/
│   ├── preprocess.py
│   ├── train.py
│   ├── evaluate.py
│   └── inference.py
├── utils/
│   ├── data_utils.py
│   ├── model_utils.py
│   └── train_utils.py
├── web/
│   ├── app.py
│   ├── templates/
│   └── static/
├── requirements.txt
├── README.md
└── .gitignore

Installation

1. Clone the Repository:

   git clone https://github.com/bayrameker/my_llm_projects.git
   cd my_llm_projects

2. Create a Virtual Environment:

   python -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Dependencies:

   pip install -r requirements.txt

Data Preprocessing

Use the preprocess.py script to preprocess your dataset.

python scripts/preprocess.py --input_file data/raw/dataset.csv --output_dir data/processed --text_column text

You can also use the data_preprocessing.ipynb notebook for an interactive approach.

Model Training

Train your model using the train.py script.

python scripts/train.py --model_name gpt2 --train_file data/processed/train.csv --output_dir models/gpt2 --epochs 3 --batch_size 4

Web Interface

Run the web interface using Flask.

cd web
python app.py

Notebooks

• Data Preprocessing: notebooks/data_preprocessing.ipynb
• Model Training: notebooks/model_training.ipynb
• Evaluation: notebooks/evaluation.ipynb
• Inference: notebooks/inference.ipynb

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or suggestions.

License

This project is licensed under the MIT License. See the LICENSE file for details.

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