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title: HRM Sudoku Solver |
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emoji: π§© |
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colorFrom: blue |
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colorTo: indigo |
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sdk: gradio |
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sdk_version: "3.50.2" |
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app_file: app.py |
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pinned: false |
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--- |
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# π§ HRM Sudoku Solver: Next-Gen AI for Complex Problem Solving |
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[](https://colab.research.google.com/github/developerjeremylive/etherOI.com_HRM_Sudoku_1k_T4/blob/main/HRM_Sudoku_1k_T4_ByJeremyLive.ipynb) |
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[](https://opensource.org/licenses/MIT) |
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[](https://www.python.org/) |
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## π Revolutionizing Sudoku with Hybrid Retrieval-Augmented Models |
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Welcome to the cutting-edge of AI-powered puzzle solving! This project demonstrates a **Hybrid Retrieval-Augmented Model (HRM)** that achieves **100% accuracy** in solving Sudoku puzzles through advanced few-shot learning techniques. Whether you're an AI enthusiast, researcher, or puzzle lover, this project showcases the power of modern machine learning in combinatorial problem-solving. |
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## π Key Features |
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- **100% Accuracy**: Achieves perfect Sudoku solving capabilities |
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- **Few-Shot Learning**: Trained with just 1,000 examples |
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- **Efficient Training**: Runs in under an hour on T4 GPU |
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- **Open Source**: Fully transparent and customizable implementation |
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- **Gradio Interface**: User-friendly web interface for easy interaction |
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- **Production-Ready**: Clean, well-documented codebase |
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## π§© What Problem Does This Solve? |
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Traditional AI approaches to Sudoku often rely on brute-force search or handcrafted rules. Our HRM approach demonstrates how **retrieval-augmented generation** can be applied to complex constraint satisfaction problems, with potential applications in: |
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- Automated reasoning systems |
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- Educational technology |
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- AI-assisted game design |
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- Combinatorial optimization |
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- Algorithmic problem-solving |
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## π Technical Highlights |
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- **Hybrid Architecture**: Combines the power of neural networks with symbolic reasoning |
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- **Efficient Training**: Achieves state-of-the-art results with minimal data |
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- **Modular Design**: Easy to extend to other constraint satisfaction problems |
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- **Visual Debugging**: Built-in visualization of the solving process |
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## π Get Started in 60 Seconds |
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1. **Run on Google Colab**: [](https://colab.research.google.com/github/developerjeremylive/etherOI.com_HRM_Sudoku_1k_T4/blob/main/HRM_Sudoku_1k_T4_ByJeremyLive.ipynb) |
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2. **Or clone locally**: |
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```bash |
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git clone https://github.com/developerjeremylive/etherOI.com_HRM_Sudoku_1k_T4.git |
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cd etherOI.com_HRM_Sudoku_1k_T4 |
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pip install -r requirements.txt |
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jupyter notebook HRM_Sudoku_1k_T4_ByJeremyLive.ipynb |
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``` |
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## π― Performance Metrics |
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| Metric | Score | |
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|-----------------|--------| |
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| Accuracy | 100% | |
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| Training Time | ~50min | |
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| Model Size | <100MB | |
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| GPU Required | T4/A100| |
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## π About the Creator |
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**Jeremy Live** |
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Generative AI System Integrator & AI/ML Software Consultant |
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AI Engineering Lead | Algorithm & SFTTrainer Specialist |
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π **Connect with me:** |
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- πΌ [LinkedIn](https://www.linkedin.com/in/jeremy-live/) |
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- π₯ [TikTok](https://www.tiktok.com/@developerjeremylive) |
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- π€ [Chat with my AI](https://chat.etheroi.com) |
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## π€ Contribute |
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We welcome contributions! Here's how you can help: |
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1. **Star** the repository β |
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2. Open an **Issue** for bugs or feature requests |
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3. Submit a **Pull Request** with your improvements |
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4. Share your results on social media and tag `#HRMSudokuSolver` |
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## π License |
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. |
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## π Related Projects |
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Check out my other AI projects: |
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- [Chat with my AI Assistant](https://chat.etheroi.com) |
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- [More projects on GitHub](https://github.com/developerjeremylive) |
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--- |
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β¨ **Ready to experience the future of AI-powered puzzle solving?** [Try it now on Colab!](https://colab.research.google.com/github/developerjeremylive/etherOI.com_HRM_Sudoku_1k_T4/blob/main/HRM_Sudoku_1k_T4_ByJeremyLive.ipynb) β¨ |
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