---
title: sim-datasets-bak
canonical_url: "https://www.modelscope.cn/datasets/scientific-intelligent-modelling/sim-datasets-bak"
md_url: "https://www.modelscope.cn/datasets/scientific-intelligent-modelling/sim-datasets-bak.md"
repository: scientific-intelligent-modelling/sim-datasets-bak
chinese_name: "科学智能建模-符号回归数据集"
last_updated: 2025-11-10
license: gpl-3.0
downloads: 19745
stars: 0
---

# sim-datasets-bak

> sim-datasets-bak - scientific-intelligent-modelling 在 ModelScope 开源的数据集。规范化了srbench, srsd, llm-srbench共719个数据集，分别包含formula.py train.csv valid.csv id_test.csv ood_test.csv metadata.yaml

scientific-intelligent-modelling/sim-datasets-bak 是 ModelScope 魔搭社区上的数据集，采用 gpl-3.0 许可。

- **Repository**: scientific-intelligent-modelling/sim-datasets-bak
- **License**: gpl-3.0
- **Downloads**: 19745
- **Stars**: 0
- **Last updated**: 2025-11-10

Source: https://www.modelscope.cn/datasets/scientific-intelligent-modelling/sim-datasets-bak

---

# SIM-Datasets: A Unified Symbolic Regression Benchmark

> A standardized benchmark collection designed for the Scientific Intelligent Modelling (SIM) toolkit, providing comprehensive datasets for symbolic regression research and applications.

## Overview

SIM-Datasets serves as a unified benchmark for symbolic regression tasks, offering standardized datasets with consistent formatting and evaluation protocols. This collection is specifically curated to support the Scientific Intelligent Modelling ecosystem, enabling researchers and practitioners to develop, test, and compare symbolic regression algorithms effectively.

## Installation

### Method 1: Git Clone

Clone the repository from Hugging Face:

```bash
git lfs install
git clone https://huggingface.co/datasets/scientific-intelligent-modelling/sim-datasets
```

Or from ModelScope (for users in China):

```bash
git lfs install
git clone https://www.modelscope.cn/datasets/scientific-intelligent-modelling/sim-datasets.git
```

### Method 2: Python Package

Install via pip for seamless integration:

```bash
pip install sim-datasets
```

## License

This project is licensed under the GPL-3.0 License. See the LICENSE file for details.

## Contributing

We welcome contributions! Please feel free to submit issues or pull requests to help improve this benchmark collection.