--- 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. ## 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.