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---
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. |