datasets:
- semeru/code-code-CodeCompletion-TokenLevel-Python
metrics:
- perplexity
base_model:
- openai-community/gpt2
Python Code Completion Model (GPT-2)
This project contains a web-based interface for a Python code completion model developed using HuggingFace. The model is based on GPT-2 and trained on the semeru/code-code-CodeCompletion-TokenLevel-Python dataset. Users can interact with the model via a Streamlit web interface.
Project Overview
This project aims to develop a model for automatic Python code completion. The GPT-2 model used here has been optimized to understand and complete Python code. The model analyzes the code written by the user and suggests relevant completions.
Features
- Model: GPT-2 based, Python code completion
- Dataset: semeru/code-code-CodeCompletion-TokenLevel-Python
- Web Interface: Streamlit
- Platform: HuggingFace
- Code Completion: Automatic Python code suggestions
Installation
1.Clone the repository:
git clone https://github.com/your_username/code-completion-model.git cd code-completion-model
2.Install the required dependencies:
pip install -r requirements.txt
3.To upload your model to HuggingFace, you can use transformers-cli:
transformers-cli login transformers-cli upload ./path_to_your_model
4.Start the Streamlit app:
streamlit run app.py
Contributers
Talha Dağlayan - talhad1109@hotmail.com Ramiz Can Akbıyık - ramizcanakbiyik@gmail.com