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| title: Mathematics Problem Solver | |
| emoji: 🧮 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 4.8.0 | |
| app_file: app.py | |
| pinned: false | |
| hardware: | |
| accelerator: a100 | |
| gpu: true | |
| python_packages: | |
| - "torch>=2.0.0" | |
| - "transformers>=4.30.0" | |
| - "accelerate>=0.20.0" | |
| - "peft==0.5.0" | |
| - "numpy>=1.21.0" | |
| # Mathematics Problem Solver | |
| This Space demonstrates our fine-tuned math model for solving various mathematical problems, with a focus on derivatives. Compare solutions between: | |
| 1. Base Model: HuggingFaceTB/SmolLM2-1.7B-Instruct | |
| 2. Our Fine-tuned Model: Joash2024/Math-SmolLM2-1.7B | |
| ## Features | |
| - Side-by-side comparison of base and fine-tuned models | |
| - Performance monitoring: | |
| - Response times | |
| - Success rates | |
| - Problem type distribution | |
| - Support for various problems: | |
| - Derivatives | |
| - Addition | |
| - Roots | |
| - Custom problems | |
| ## Technical Details | |
| - A100 GPU acceleration | |
| - Float16 precision for efficient inference | |
| - LaTeX notation support | |
| - Real-time performance tracking | |