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Llama 2: Early Adopters' Utilization of Meta's New Open Source Pretrained Model

Llama 2: Early Adopters' Utilization of Meta's New Open-Source Pretrained Model

Dec 05, 20251 min read

tags
  • lit
link
https://www.preprints.org/manuscript/202307.2142/v1
zotero
zotero://select/library/items/7AEYNMFU
itemType
preprint
authors
  • Dimitrios K. Nasiopoulos
  • Nikolaos D. Tselikas
  • Dimitrios K. Nasiopoulos
pubDate
2023-08-01
retDate
2025-12-05
relatedProjects
null
tlkr
null

Abstract

The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of innovative open-source pre-trained models, fostering advancements in various applications. One such model is Llama 2, an open-source pre-trained model released by Meta, which has garnered significant attention among early adopters. In addition to exploring the foundational elements of the Llama v2 model, this paper investigates how these early adopters leverage the capabilities of Llama 2 in their AI projects. Through a qualitative study, we delve into the perspectives, experiences, and strategies employed by early adopters to leverage Llama 2’s capabilities. The findings shed light on the model’s strengths, weaknesses, and areas of improvement, offering valuable insights for the AI community and Meta to enhance future model iterations. Additionally, we discuss the implications of Llama 2’s adoption on the broader open-source AI landscape, addressing challenges and opportunities for developers and researchers in the pursuit of cutting-edge AI solutions. The present study constitutes an early exploration of the Llama 2 pre-trained model, holding promise as a foundational basis for forthcoming research investigations.


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