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This project is a Flask-based web application that integrates a fine-tuned language model to provide conversational AI capabilities.

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zacharias1219/finetuned-custom-llm-model

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Intel Final Project

This project is a Flask-based web application that integrates a fine-tuned language model to provide conversational AI capabilities. The application uses HTML, CSS, and JavaScript for the front-end, and Python for the back-end, leveraging the transformers library for model handling.

Features

  • Interactive chat interface with a chatbot.
  • Fine-tuned language model for generating responses.
  • Dockerized deployment for easy setup and scaling.
  • Dark-themed UI with responsive design.

Prerequisites

  • Python 3.7 or higher
  • Docker (optional, for containerized deployment)
  • NVIDIA GPU with CUDA (optional, for faster inference)

Installation

1. Clone the Repository

git clone https://github.com/zacharias1219/finetuned-custom-llm-model.git
cd finetuned-custom-llm-model

2. Set Up the Virtual Environment

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

3. Install the Required Packages

pip install -r requirements.txt

4. Download and Place the Fine-Tuned Model

Place your fine-tuned model files in a directory named finetuned_model within the project directory. Ensure the directory contains the following files:

  • config.json
  • generation_config.json
  • model-00001-of-00006.safetensors
  • model-00002-of-00006.safetensors
  • model-00003-of-00006.safetensors
  • model-00004-of-00006.safetensors
  • model-00005-of-00006.safetensors
  • model-00006-of-00006.safetensors
  • model.safetensors.index.json
  • special_tokens_map.json
  • tokenizer_config.json
  • tokenizer.json
  • tokenizer.model

5. Run the Application

python app.py

Open your web browser and navigate to http://127.0.0.1:5000 to interact with the chatbot.

Docker Deployment

1. Build the Docker Image

docker build -t chatbot-app .

2. Run the Docker Container

docker run -p 5000:5000 chatbot-app

Open your web browser and navigate to http://127.0.0.1:5000 to interact with the chatbot.

Usage

  1. Start the application by running python app.py or using Docker as described above.
  2. Open your web browser and go to http://127.0.0.1:5000.
  3. Type your message in the chat interface and press the send button to interact with the chatbot.

Project Structure

├── app.py                     # Main application file
├── Dockerfile                 # Dockerfile for containerized deployment
├── requirements.txt           # Python dependencies
├── templates
│   └── chat.html              # HTML template for the chat interface
├── static
│   ├── styles.css             # CSS file for styling
│   └── images                 # Directory for image assets
└── finetuned_model            # Directory containing the fine-tuned model files

License

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

Acknowledgements

There are some file that are missing as it is too big to upload on github so here are the photos

Screenshot 2024-07-14 223850

Screenshot 2024-07-14 223857

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This project is a Flask-based web application that integrates a fine-tuned language model to provide conversational AI capabilities.

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