Topic

Unsloth Fine Tuning

Coverage tagged unsloth fine tuning.

Articles: 1
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Data graphic: fine-tuning Qwen 2.5 32B with Unsloth and 4-bit QLoRA takes 20.8GB of VRAM for the whole training pipeline, against upwards of 120GB for standard 16-bit fine-tuning, leaving 3.2 GB free on a 24 GB GPU. The budget splits into about 14.8 GB of 4-bit base weights, 2.8 GB of activations and KV cache, 2.2 GB of CUDA context, 0.65 GB of optimizer states and 0.35 GB of LoRA adapters, alongside hyperparameter targets such as LoRA rank 16 or 32 and a learning rate of 1e-4 to 2e-4.

stableResearch Unsloth Fine Tuning

Fine-Tuning 27B–32B LLMs on a Single 24GB GPU: Unsloth and 4-Bit QLoRA Production Guide

Learn how to fine-tune 27B–32B LLMs like Qwen 2.5 on a single 24GB GPU using Unsloth and 4-bit QLoRA with full code, memory optimization, and serving guides.

Aug 15 · 7 min