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