AI8 min read
Fine-Tuning LLaMA 3.3 on Custom Datasets using QLoRA and Unsloth
By Sayyed Abrar Akhtar • Published 2025-02-21
Step-by-step guide to parameter-efficient fine-tuning (PEFT) on consumer GPU instances.
Quantized Low-Rank Adaptation (QLoRA) reduces GPU memory demands by 80%. Using Unsloth acceleration frameworks allows fine-tuning 8B and 70B parameter models on accessible cloud instances like NVIDIA T4/A100.
Tags:#Fine-Tuning#LLaMA#PyTorch