Gen AI Content Generation Model Using LLM Without Internet

The Gen AI content generation model uses the LLAMA-3.1-8B model where 8B implies 8 billion parameters to effectively produce customized content. It generates the content based on three inputs: topic, word count, and complexity level, which can be easy, medium, or hard. The front-end development is done by using Streamlit and CSS-based interface to make the model user-friendly. Backend functions are supported by LangChain and CTransformers modules for proper communication. It is totally an offline-working model that minimizes reliance on servers or even internet access in favor of increased security. This pre-training will have been extensive over datasets that try to uncover all patterns while the fine-tuning is toward applications in various tasks, thereby perfecting text summarization, question answering, content generation, or even classification tasks.

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Publication Details

Journal
Global Journal of Engineering Innovations and Interdisciplinary Research
Published
2025-06-27
DOI
https://doi.org/10.33425/3066-1226.1131
Primary Topic
Technology and Data Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Gen AI Content Generation Model Using LLM Without Internet

Shiva Kumar, СЕДЫХ О.Г. СЕДЫХ О.Г., B. Ravikrishna, Vinuthna Taduru et al.
Global Journal of Engineering Innovations and Interdisciplinary Research
Technology and Data Analysis
article

Gen AI Content Generation Model Using LLM Without Internet

Shiva Kumar, СЕДЫХ О.Г. СЕДЫХ О.Г., B. Ravikrishna, Vinuthna Taduru, Arvind Reddy Ravula
article en

Abstract

The Gen AI content generation model uses the LLAMA-3.1-8B model where 8B implies 8 billion parameters to effectively produce customized content. It generates the content based on three inputs: topic, word count, and complexity level, which can be easy, medium, or hard. The front-end development is done by using Streamlit and CSS-based interface to make the model user-friendly. Backend functions are supported by LangChain and CTransformers modules for proper communication. It is totally an offline-working model that minimizes reliance on servers or even internet access in favor of increased security. This pre-training will have been extensive over datasets that try to uncover all patterns while the fine-tuning is toward applications in various tasks, thereby perfecting text summarization, question answering, content generation, or even classification tasks.

Global Journal of Engineering Innovations and Interdisciplinary ResearchVol. 5(4)
Vignan's Foundation for Science, Technology & Research (IN), Vignana Jyothi Institute of Management (IN)
Openalex Percentile: Top 73%
Technology and Data Analysis
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