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https://github.com/ansh-info/transformers-explained
A dynamic, interactive React application for understanding transformer architecture and its components. Built with React, Tailwind CSS, and Recharts, this app provides intuitive visualizations of self-attention mechanisms, architectural comparisons, and performance metrics.
https://github.com/ansh-info/transformers-explained
ai architecture artificial-intelligence chatgpt deep-learning embeddings gpt llama lucide-icons lucide-react neural-network ollama openai react recharts self-attention tailwindcss transformer transformers
Last synced: 8 days ago
JSON representation
A dynamic, interactive React application for understanding transformer architecture and its components. Built with React, Tailwind CSS, and Recharts, this app provides intuitive visualizations of self-attention mechanisms, architectural comparisons, and performance metrics.
- Host: GitHub
- URL: https://github.com/ansh-info/transformers-explained
- Owner: ansh-info
- License: mit
- Created: 2024-11-06T13:34:03.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2024-11-06T14:08:22.000Z (about 2 months ago)
- Last Synced: 2024-12-22T01:55:45.491Z (12 days ago)
- Topics: ai, architecture, artificial-intelligence, chatgpt, deep-learning, embeddings, gpt, llama, lucide-icons, lucide-react, neural-network, ollama, openai, react, recharts, self-attention, tailwindcss, transformer, transformers
- Language: JavaScript
- Homepage:
- Size: 513 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Transformer Architecture Interactive Visualization
An interactive web application built with React to help understand the Transformer architecture, its evolution, and its impact on modern AI. This project provides visual explanations of key concepts in transformer models, including self-attention mechanisms, architectural comparisons, and performance metrics.
#### Transformer Architecture
## 🌟 Features
- **Interactive Timeline**: Visualize the evolution of transformer architecture
- **Architecture Visualization**: Animated diagram of encoder-decoder structure
- **Self-Attention Demo**: Live visualization of attention mechanisms
- **Performance Metrics**: Compare different transformer models
- **Comparative Analysis**: RNN vs LSTM vs Transformer architecture
- **Responsive Design**: Works seamlessly on desktop and mobile devices
#### Performance Metrics
## 🚀 Getting Started
### Prerequisites
- Node.js (v14 or higher)
- npm (v6 or higher)
### Installation
1. Clone the repository:
```bash
git clone https://github.com/ansh-info/Transformers-Explained.git
cd Transformers-Explained
```
2. Install dependencies:
```bash
npm install
```
3. Start the development server:
```bash
npm start
```
The application will be available at `http://localhost:3000`
## 📦 Project Structure
```
src/
components/
ui/
card.js # Basic card components
tabs.js # Tab navigation components
sections/
ArchitectureComparison.js # Architecture comparison visualizations
Timeline.js # Historical timeline
WhyTransformers.js # Explanation of transformer benefits
visualizations/
ArchitectureAnimation.js # Animated architecture diagram
AttentionVisualizer.js # Self-attention mechanism demo
PerformanceChart.js # Performance metrics charts
App.js # Main application component
```
## 🛠️ Built With
- [React](https://reactjs.org/) - Frontend framework
- [Tailwind CSS](https://tailwindcss.com/) - Styling
- [Recharts](https://recharts.org/) - Data visualization
- [Lucide React](https://lucide.dev/) - Icons
- [Create React App](https://create-react-app.dev/) - Project setup
## 📚 Key Components
### Architecture Tab
- Displays the encoder-decoder structure
- Interactive visualization of transformer components
- Comparative analysis with other architectures
### Self-Attention Tab
- Live demonstration of attention mechanism
- Query, Key, Value explanation
- Interactive attention weights visualization
### Applications Tab
- Timeline of transformer development
- Real-world applications
- Use cases and examples
### Performance Tab
- Comparative metrics
- Performance charts
- Model comparisons
## 🎨 Customization
### Adding New Visualizations
1. Create a new component in `src/components/visualizations`
2. Import and add to the relevant tab in `App.js`
3. Add any necessary styles to Tailwind config
### Modifying Themes
Update the Tailwind configuration in `tailwind.config.js`:
```javascript
module.exports = {
content: ["./src/**/*.{js,jsx,ts,tsx}"],
theme: {
extend: {
// Add custom colors, spacing, etc.
},
},
plugins: [],
}
```
## 🤝 Contributing
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## 📝 License
This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
## 🙏 Acknowledgments
- Inspired by the paper "Attention Is All You Need"
- Built upon the work of the transformer architecture creators
- Community contributions and feedback
## 🔮 Future Improvements
- [ ] Add more interactive animations
- [ ] Include code examples
- [ ] Add more architectural variants
- [ ] Implement interactive training visualization
- [ ] Add multilingual support
---