This repository contains the implementation of a fine-tuned Llama2 chatbot using QLoRA, tailored to provide detailed information and recommendations about movies. The model is fine-tuned on the IMDB dataset, enabling it to generate informed and contextually relevant responses.
- Movie Information: The chatbot can fetch and provide detailed information about a wide range of movies, including plot summaries, cast details, directorial information, and more.
- Movie Recommendations: Based on user preferences and querying style, the chatbot offers personalized movie recommendations.
- Dynamic Context Handling: The model uses a predefined context during inference to generate accurate and relevant responses. If the information required to answer a query is not available, the chatbot smartly responds with "I don't know," prompting further clarification or a different query from the user.
- Base Model: Llama2
- Training Data: IMDB dataset
- Technique: Fine-tuning with QLoRA for query-focused responses
To set up the chatbot on your local machine, follow these steps:
- Clone the Repository:
git clone https://github.com/yourgithubusername/llama2-movie-chatbot.git
- Install Dependencies:
pip install -r requirements.txt
- Run the Application:
python app.py
To interact with the chatbot:
- Start the application using the above instructions.
- Access the chat interface through your local web server (usually
http://localhost:5000). - Type your movie-related questions or ask for recommendations in the chat interface.
Contributions to enhance the functionality or efficiency of the Llama2 movie chatbot are welcome. Please follow these steps:
- Fork the repository.
- Create your feature branch (
git checkout -b feature/AmazingFeature). - Commit your changes (
git commit -m 'Add some AmazingFeature'). - Push to the branch (
git push origin feature/AmazingFeature). - Open a Pull Request.
Feel free to adjust the content to better fit your project's specifics or personal preferences!