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README.md

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+# DIVE Lab at TAMU
+
+Welcome to the Hugging Face organization for the DIVE Lab at Texas A&M University. We strive to seek synergies between foundational and use-inspired themes. Our foundational research centers on developing innovative models and algorithms in the fields of machine learning, geometric deep learning, language models and agents. Our use-inspired research aims at tackling challenges in various scientific and engineering disciplines, including physics-informed modeling and simulations, biology, drug discovery, quantum physics and chemistry, materials science, molecular dynamics and simulation, fluid dynamics, and partial differential equations, among others.
+
+The datasets available in our Hugging Face repository are described below:
+
+**Sys2Bench**
+
+Sys2bench is a benchmark designed to evaluate Large Language Models’ reasoning and plannning abilities across arithmetic, logical, common, algorithmic reasoning and planning.
+
+Link: https://huggingface.co/datasets/dive-lab/Sys2Bench
+
+**ShockCast**
+
+Link: https://huggingface.co/datasets/dive-lab/ShockCast
+
+**PubChemQCR**
+
+PubChemQCR is a dataset that contains the DFT relaxation trajectory of ~3.5 million small molecules, which can facilitate the development of machine learning interatomic potential (MLIP) models.
+
+Link: https://huggingface.co/datasets/dive-lab/PubChemQCR
+
+---
+
+All other scientific and engineering projects from our lab can be found at the following link:
+
+**Artificial Intelligence Research for Science (AIRS)**: https://github.com/divelab/AIRS/tree/main
+
+## Connect
+
+- [GitHub](https://github.com/divelab)
+- [Website](http://people.tamu.edu/~sji/)
+
+
+