https://github.com/muavia1/psuedocode-to-code-generation-using-transformers-architecture-using-pytorch
PsuedoCode2Code is a transformer-based deep learning model that translates human-readable pseudocode into programming code. This project aims to assist developers, students, and educators by providing a structured way to convert psuedo code to c++ code.
https://github.com/muavia1/psuedocode-to-code-generation-using-transformers-architecture-using-pytorch
code-generation gradio model-learning model-training python pytorch transformer
Last synced: 3 months ago
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PsuedoCode2Code is a transformer-based deep learning model that translates human-readable pseudocode into programming code. This project aims to assist developers, students, and educators by providing a structured way to convert psuedo code to c++ code.
- Host: GitHub
- URL: https://github.com/muavia1/psuedocode-to-code-generation-using-transformers-architecture-using-pytorch
- Owner: Muavia1
- Created: 2025-03-08T11:43:01.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-08T11:56:47.000Z (3 months ago)
- Last Synced: 2025-03-08T12:27:11.647Z (3 months ago)
- Topics: code-generation, gradio, model-learning, model-training, python, pytorch, transformer
- Language: Jupyter Notebook
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# PsuedoCode-to-Code-Generation-using-Transformers-Architecture-using-PyTorch
**PsuedoCode2Code** is a transformer-based deep learning model that translates human-readable pseudocode into programming code. This project aims to assist developers, students, and educators by providing a structured way to convert psuedo code to c++ code.
## Features
- Utilizes a transformer architecture for sequence-to-sequence translation.
- Supports tokenization and vocabulary building for both code and pseudocode.
- Implements positional encoding and attention mechanisms to enhance translation accuracy.
- Uses PyTorch for efficient model training and inference.
## Installation
Clone the repository and install the dependencies:
```bash
pip install -r requirements.txt
```
## Requirements
- Python 3.x
- PyTorch
- Pandas
- tqdm
## Contributing
Contributions are welcome! Feel free to submit issues or pull requests.
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