Year: 2024
Type: article
Abstract: The development and deployment of a Large Language Model (LLM)-based tool designed to generate human-like responses to natural language inputs in a network isolated environment presents unique technical and logistical challenges. Such a tool leverages state-of-the-art Natural Language Processing (NLP) and machine learning techniques to simulate real-time, coherent, and contextually appropriate interactions without relying on an active internet connection. This approach involves training or fine-tuning a pre-existing LLM on domain-specific datasets and configuring the model to operate efficiently on limited resources, addressing the constraints of an offline deployment. The solution provides an autonomous conversational agent capable of supports text summarization, upload CSV and PDF files. The tools used for this project Natural Language Processing(NLP), Hugging face. Key components include model optimization to reduce computational overhead, storage requirements, and latency in response generation. Future scope includes improving model robustness and incorporating ethical guardrails to ensure the responsible use of LLMs, especially in sensitive fields such as healthcare, education, and customer support.
DOI: 10.55041/ijsrem40033
Authors: Antony Roshan R, Barath V, Deva Dharshini D, Dhilak M, Saraswathi R
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4405739472