A Unified Optimization Framework for Large Language Models in Enterprise Applications Using Python

Authors

  • Bhasker Reddy Ande

Keywords:

Large Language Models, Python, Optimization, Enterprise Applications, Low-Rank Adaptation, Reinforcement Learning, Retrieval-Augmented Generation, AI.

Abstract

The recent advancements in Large Language Models (LLMs), such as GPT-4, haverevolutionized various enterprise applications, from customer service automation to data analysisand decision-making.

References

Achiam, J., Adler, S., Agarwal, S., Ahmad, L., Akkaya, I., Aleman, F.L., Almeida, D.,

Altenschmidt, J., Altman, S., Anadkat, S., & Avila, R. (2023). GPT-4 technical report.

arXiv preprint arXiv:2303.08774. https://arxiv.org/abs/2303.08774

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Published

2024-06-19

How to Cite

Bhasker Reddy Ande. (2024). A Unified Optimization Framework for Large Language Models in Enterprise Applications Using Python . Journal of Computational Analysis and Applications (JoCAAA), 33(06), 2111–2122. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2973

Issue

Vol. 33 No. 06 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.