Best Practices for Using Llama 2 Chat LLM with SageMaker: A Comparative Study

Registration ID: IJNRD_226644

Published ID: IJNRD2406503

DOI: Click Here to Get

ER. PRONOY CHOPRA , SHALU JAIN , DR. POORNIMA TYAGI

Llama 2, Amazon SageMaker,, Large Language Models (LLMs), Conversational AI, Model Deployment, Performance Optimization, Scalability, Cost-Effectiveness, Machine Learning, Cloud Computing, Inference Optimization, Security Considerations.

The integration of large language models (LLMs) like Llama 2 into cloud-based machine learning platforms such as Amazon SageMaker presents a significant opportunity for advancing conversational AI applications. This paper explores the best practices for deploying and optimizing Llama 2 Chat, an advanced language model, within the SageMaker environment. Through a comparative study, we analyze the performance, scalability, and cost-effectiveness of different deployment strategies, focusing on the unique capabilities of SageMaker that can enhance Llama 2’s functionalities. We investigate several key areas, including model training, inference optimization, resource management, and security considerations. By leveraging SageMaker’s robust features such as automated model tuning, elastic infrastructure, and integrated security, we aim to provide insights into achieving optimal performance and efficiency when utilizing Llama 2 Chat. Our study includes practical experiments and benchmarks to illustrate the impact of various configurations on model latency, throughput, and cost. The findings offer valuable guidance for developers and organizations aiming to implement Llama 2 in real-world applications, ensuring a balance between computational efficiency and conversational quality. This paper contributes to the growing body of knowledge on LLM deployment in cloud environments, providing

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ER. PRONOY CHOPRA , SHALU JAIN, & DR. POORNIMA TYAGI (June-2024). Best Practices for Using Llama 2 Chat LLM with SageMaker: A Comparative Study. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(6), f121-f139. https://ijnrd.org/papers/IJNRD2406503.pdf

Volume 9 Issue 6, June-2024

Pages : f121-f139

Paper Reg. ID: IJNRD_226644

Published Paper Id: IJNRD2406503

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Research Area: Engineering

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2406503.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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