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| title: CodeCraftLab | |
| emoji: π | |
| colorFrom: pink | |
| colorTo: purple | |
| sdk: streamlit | |
| sdk_version: 1.43.2 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: A fine-tuning platform | |
| datasets: | |
| - angie-chen55/python-github-code | |
| - sdiazlor/python-reasoning-dataset | |
| - MatrixStudio/Codeforces-Python-Submissions | |
| # CodeGen Hub π | |
| [](https://replit.com/@replit/CodeGen-Hub)   | |
| A streamlined platform for training and using code generation models with Hugging Face integration π€ | |
| ## β¨ Features | |
| - π Upload and preprocess Python code datasets | |
| - π οΈ Configure and train models with customizable parameters | |
| - π‘ Generate code predictions using trained models | |
| - π Monitor training progress with visualizations | |
| - π Seamless integration with Hugging Face Hub | |
| ## π Getting Started | |
| 1. Run the Streamlit app | |
| 2. Upload your Python code dataset in the Dataset Management section | |
| 3. Train your model in the Model Training section | |
| 4. Generate code using your trained models in the Code Generation section | |
| ## π οΈ Technology Stack | |
| - Streamlit for the web interface | |
| - PyTorch for model training | |
| - Hugging Face Transformers for code generation | |
| - Pandas for data handling | |
| - Plotly for visualizations | |
| ## π» Development | |
| Run linting and tests: | |
| ```bash | |
| ./scripts/lint.sh | |
| ``` | |
| ## π License | |
| MIT License - feel free to use and modify! | |
| ## π€ Contributing | |
| Contributions welcome! Please check our contribution guidelines. | |
| --- | |
| Made with π using [Replit](https://replit.com) |