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This project aims to create a personalized AI assistant based on the LLaMA 3 8B model. The AI will be fine-tuned using personal data, including professional experiences, educational background, skills, projects, and publications, to provide accurate and personalized responses about the individual. The assistant will be deployed on a personal portfolio website to interactively engage with recruiters and visitors, offering detailed insights in a human-like manner.

Motivation and Significance:

In the competitive professional landscape, a dynamic and interactive portfolio can significantly enhance an individual's digital presence. By integrating a personalized AI assistant, this project seeks to:

Enhance Recruiter Engagement: Allow recruiters to interactively query and receive detailed, personalized responses about the individual's background and achievements.
Showcase Technical Proficiency: Highlight the project owner's skills in AI and machine learning through a cutting-edge application.
Improve User Experience: Offer visitors a more interactive and engaging way to learn about the project owner compared to static text.
The fine-tuning process for the LLaMA 3 8B model requires substantial computational resources due to the model's size and complexity. Specifically, the project requires:

High-Performance GPUs: To efficiently handle the computational demands of fine-tuning the 8 billion parameter model.
Extended Training Time: Adequate GPU time to ensure the model can be properly trained on the personalized dataset.
Memory and Storage: Sufficient memory and storage capacity to manage the large model and dataset.
Expected Outcomes:

A fully functional AI assistant capable of providing personalized, contextually accurate responses.
Enhanced engagement on the personal portfolio website, providing a unique user experience.
Demonstration of practical application of advanced AI technologies in personal branding and professional presentation.