Fine-tuning LLMs on PyChrono-specific data improves their success rate at generating runnable simulation code from about 40% to about 85%, compared to prompting general models.
https://arxiv.org/abs/2408.11987
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ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono
Fine-tuning LLMs on PyChrono-specific data improves their success rate at generating runnable simulation code from about 40% to about 85%, compared to prompting general models.