---
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.