diff --git "a/README.md" "b/README.md" --- "a/README.md" +++ "b/README.md" @@ -1,11 +1,7245 @@ --- -license: Apache License 2.0 +license: gpl-3.0 +tags: +- symbolic-regression +- scientific-discovery +- benchmark +- srsd +- srbench +- llm-srbench +pretty_name: 'sim-datasets: a benchmark for Scientific Intelligent Modeling' +size_categories: +- 100M A standardized benchmark collection designed for the Scientific Intelligent Modelling (SIM) toolkit, providing comprehensive datasets for symbolic regression research and applications. -#### 下载方法 -:modelscope-code[]{type="sdk"} -:modelscope-code[]{type="git"} +## 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. \ No newline at end of file