AI2025
CodeMaverick Fine-tuning
Large Language Model fine-tuning with PEFT and QLoRA
RoleAI Developer
Year2025
StackPython, Hugging Face, PEFT
Overview
Fine-tuning LLMs on the Kaggle platform to create lightweight, task-optimized models.
Problem
General-purpose LLMs are often too large for edge deployment or specific niche tasks.
Solution
Applied 4-bit quantization and Parameter-Efficient Fine-Tuning (PEFT/QLoRA) to reduce model size while maintaining performance.
Process
Performed full data preprocessing, tokenization, and built the training pipeline from scratch.
Architecture
Hugging Face Transformers library integrated with QLoRA for efficient training on consumer-grade hardware.
Tech Stack
PythonHugging FacePEFTQLoRAKaggle
Outcome & Results
Exported a lightweight LLM ready for fast, production-grade inference.