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--- |
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license: apache-2.0 |
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tags: |
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- geometry |
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- problem-solving |
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- multi-modal |
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- pytorch |
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--- |
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# PGPS: A Neural Geometric Solver |
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## Model Description |
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PGPS (Plane Geometry Problem Solver) is a neural geometric solver that uses multi-modal information through structural and semantic pre-training to solve plane geometry problems. This model was introduced in the IJCAI 2023 paper and represents the pre-trained language model component of the PGPSNet architecture. |
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## Model Details |
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- **Model Type:** Pre-trained Language Model for Geometric Problem Solving |
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- **Model File:** `LM_MODEL.pth` |
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- **File Size:** ~64MB |
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- **Framework:** PyTorch |
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- **Paper:** [PGPS: A Neural Geometric Solver at IJCAI 2023](https://www.ijcai.org/proceedings/2023/) |
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- **Original Repository:** [https://github.com/mingliangzhang2018/PGPS](https://github.com/mingliangzhang2018/PGPS) |
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## Intended Use |
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This model is designed for: |
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- Solving plane geometry problems |
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- Parsing geometric diagrams |
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- Understanding textual clauses in geometry problems |
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- Generating solution programs for geometric problems |
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## Requirements |
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- Python 3.8 |
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- PyTorch 1.7.1 |
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- CUDA 10.2 |
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- One GTX-RTX or two TITAN Xp GPUs (for training) |
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## Installation |
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1. Clone the original repository: |
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```bash |
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git clone https://github.com/mingliangzhang2018/PGPS.git |
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cd PGPS |
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``` |
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2. Install dependencies: |
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```bash |
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pip install -r requirements.txt |
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``` |
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3. Download this pre-trained model and place it in the appropriate directory. |
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## Usage |
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### Training with Pre-trained Model |
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```python |
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python start.py --dataset Geometry3K --use_MLM_pretrain |
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``` |
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### Evaluation |
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```python |
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python start.py --dataset Geometry3K --evaluate_only --eval_method completion |
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``` |
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## Dataset |
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The model works with the PGPS9K dataset, which contains: |
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- Diagram annotations |
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- Solution programs |
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- Multi-modal geometric problem data |
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Download the dataset from the [CASIA-PGPS9K homepage](https://sites.google.com/view/pgps9k). |
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## Citation |
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If you use this model in your research, please cite: |
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```bibtex |
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@inproceedings{zhang2023pgps, |
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title={PGPS: A Neural Geometric Solver}, |
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author={Zhang, Mingliang and others}, |
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booktitle={Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23)}, |
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year={2023} |
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} |
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``` |
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## License |
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Apache 2.0 |
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## Authors |
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The original PGPS model was developed by Mingliang Zhang and colleagues. This Hugging Face repository is a mirror of the pre-trained model from the [official GitHub repository](https://github.com/mingliangzhang2018/PGPS). |
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## Acknowledgments |
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Special thanks to the PGPS team for making their pre-trained models publicly available. |
