shikharkunal / finetuning_gpt2

Fine-tuned a pre-trained Large language model(GPT-2) using a publicly available dataset to make it a proficient Question Answering Bot

Question Answering Model using GPT-2

Overview

This project is a Question Answering Model based on the GPT-2 language model by OpenAI. The model is implemented as a Jupyter Notebook, making it easy to explore, understand, and use for generating answers to user queries.

Features

• GPT-2 Model: Utilizes the GPT-2 language model, known for its advanced natural language understanding and generation capabilities.

• Question Answering: The notebook provides functionality for answering questions by interacting with the GPT-2 model.

• Fine-tuned GPT-2: This model is fine-tuned to specifically be a question answering bot, I used publicly available dataset to finetune the model.

Getting Started

1. Clone the Repository:

   git clone https://github.com/your-username/question-answering-gpt2.git
   cd Finetuning_GPT2

2. Install Dependencies: Open the Jupyter Notebook and install any required dependencies specified in the notebook.

3. Run the Notebook: Open the colab Notebook and follow the instructions provided. Execute the cells to load the model, and perform question answering.

Usage

1. Open the Colab Notebook in your google colab.

2. Follow the step-by-step instructions provided in the notebook cells.

3. Execute the cells to load the GPT-2 model, and generate answers to questions.

Contributing

Contributions to the Notebook are welcome! If you have ideas for improvements or encounter issues, feel free to open an issue or submit a pull request.

License

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

Happy questioning!