TheAnnotatedTransformer

Educational Transformer implementation based on Harvard's tutorial. Complete PyTorch code with Chinese annotations, interactive notebook, attention visualization, and translation examples. Perfect for learning NLP and deep learning concepts.

🚀 Features

• Complete Transformer Implementation: Full PyTorch implementation from "Attention Is All You Need"
• Chinese Annotations: Detailed Chinese comments for better understanding
• Interactive Notebook: Jupyter notebook with step-by-step explanations
• Attention Visualization: Visual representations of attention mechanisms
• Translation Examples: Real-world translation using Multi30k dataset

📁 Project Structure

• the_annotated_transformer.py - Complete Transformer implementation
• TheAnnotatedTransformer.ipynb - Interactive Jupyter notebook
• requirements.txt - Dependencies and packages needed

🤖 Model Files

Note: Pre-trained model files (*.pt) are not included in this repository due to their large size (each ~230MB).

How to Get the Models:

1. Option 1: Train your own models using the notebook
2. Option 2: Download pre-trained models (will be available on Hugging Face soon)
3. Option 3: Contact the repository owner for model files

Model Files Available:

• multi30k_model_00.pt through multi30k_model_07.pt - Training checkpoints
• multi30k_model_final.pt - Final trained model
• vocab.pt - Vocabulary file

🛠️ Installation

pip install -r requirements.txt

📚 Usage

See TheAnnotatedTransformer.ipynb for detailed examples and explanations.

🔬 Training

The notebook includes complete training pipeline for Multi30k German-English translation task.

📄 License

This project follows the original Harvard Annotated Transformer license.

🤝 Contributing

Feel free to submit issues and pull requests!

📞 Contact

For questions about model files or project details, please open an issue. 220242544@seu.edu.cn