https://github.com/ajay-dhangar/generative-ai-project
https://github.com/ajay-dhangar/generative-ai-project
Last synced: 7 months ago
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- Host: GitHub
- URL: https://github.com/ajay-dhangar/generative-ai-project
- Owner: ajay-dhangar
- Created: 2024-12-01T07:40:17.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-12-01T07:45:50.000Z (10 months ago)
- Last Synced: 2025-03-19T06:51:44.402Z (7 months ago)
- Language: Python
- Size: 9.77 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Generative AI Project
This project showcases various generative artificial intelligence models implemented using Python and popular libraries such as TensorFlow and PyTorch. It includes implementations of state-of-the-art models for tasks such as image and text generation.
## Table of Contents
- [Generative AI Project](#generative-ai-project)
- [Table of Contents](#table-of-contents)
- [Introduction](#introduction)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)
- [Acknowledgments](#acknowledgments)
## Introduction
Generative AI, or generative modelling, involves using machine learning techniques to generate new data instances. This project explores different generative AI techniques and provides implementations for experimentation and learning purposes.
## Features
- Implementation of various generative AI algorithms
- Experimentation with different datasets
- Applications showcasing the capabilities of generative models
## Installation
To get started with this project, follow these steps:
1. Clone this repository to your local machine:
```bash
git clone https://github.com/ajay-dhangar/generative-ai-project.git
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
## Usage
The project is organized into subdirectories, each containing implementations of different generative AI models. You can navigate to each subdirectory to explore the implementations and run the provided scripts.
Here are some examples of how to use the project:
- **Image Generation**: Navigate to the `image_generation` directory and run the `generate_images.py` script to generate synthetic images using generative adversarial networks (GANs).
- **Text Generation**: Explore the `text_generation` directory to find recurrent neural network (RNNs) implementations for text generation tasks.
Feel free to experiment with the provided code and modify it according to your requirements.
## Contributing
Contributions are welcome! If you'd like to contribute to this project, please follow these steps:
1. Fork the repository.
2. Create a new branch (`git checkout -b feature/your-feature`).
3. Make your changes.
4. Commit your changes (`git commit -am 'Add new feature'`).
5. Push to the branch (`git push origin feature/your-feature`).
6. Create a new Pull Request.
## License
This project is licensed under the MIT License - see the [LICENSE](#) file for details.
## Acknowledgments
Special thanks to [contributors](#) who have contributed to this project.