Recreating 'That Person' in AI: Fine-tuning a LLM with LINE Chat History

research #llm 📝 Blog|Analyzed: Mar 12, 2026 11:00•

Published: Mar 12, 2026 10:54

•

1 min read

Analysis

This is an exciting project demonstrating the power of Fine-tuning! By using a readily available dataset—LINE chat logs—the author successfully trained a Large Language Model to mimic a specific individual's communication style. This innovative approach makes personalized AI creation accessible even on personal GPUs like an RTX 3060.

Key Takeaways

•The project uses LINE chat history (.txt format) as the dataset.
•It employs QLoRA for efficient Fine-tuning, allowing operation on a 12GB VRAM GPU.
•The process is broken down into five Python script steps, making it modular and understandable.

Reference / Citation

View Original

"In this article, we will carefully explain the procedure for creating an AI that mimics a specific person by fine-tuning Qwen2.5-3B-Instruct with QLoRA using LINE chat history (.txt export), along with the code."

Qiita MLMar 12, 2026 10:54

* Cited for critical analysis under Article 32.

Older

Data Science Power Up: 32-64GB RAM Becoming the New Standard?

Newer

Reimagine LLM Development: A Tech Lead's Guide to Context Engineering