ChemFoundationModels/ChemLLMBench

Official Code for What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks (In NeurIPS 2023)

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Experimental

This project helps chemists and materials scientists evaluate how well large language models (LLMs) perform on various chemistry-related tasks. It takes chemical data, reaction descriptions, or molecular properties as input and uses different LLMs to predict outcomes like reaction products, retrosynthesis pathways, or molecular properties. The output helps researchers understand the strengths and weaknesses of LLMs for specific chemical challenges.

170 stars. No commits in the last 6 months.

Use this if you are a chemist or researcher wanting to compare how different large language models handle tasks like predicting chemical reactions, identifying molecules from descriptions, or evaluating molecular properties.

Not ideal if you are looking for a tool to directly perform chemical simulations or experimental analyses, as this focuses on benchmarking AI models.

computational chemistry drug discovery materials science chemical reactions molecular design
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 8 / 25

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Last pushed

Jul 26, 2024

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