no code implementations • 1 Feb 2024 • V. K. Cody Bumgardner, Mitchell A. Klusty, W. Vaiden Logan, Samuel E. Armstrong, Caylin Hickey, Jeff Talbert
This paper introduces a user-friendly platform developed by the University of Kentucky Center for Applied AI, designed to make large, customized language models (LLMs) more accessible.
no code implementations • 5 Oct 2023 • Aaron D. Mullen, Samuel E. Armstrong, Jeff Talbert, V. K. Cody Bumgardner
Machine learning classification problems are widespread in bioinformatics, but the technical knowledge required to perform model training, optimization, and inference can prevent researchers from utilizing this technology.
1 code implementation • 3 Aug 2023 • V. K. Cody Bumgardner, Aaron Mullen, Sam Armstrong, Caylin Hickey, Jeff Talbert
This paper introduces an approach that combines the language reasoning capabilities of large language models (LLMs) with the benefits of local training to tackle complex, domain-specific tasks.