Fine-tuning LLMs has become much easier because of open-source tools. You no longer need to build the full training stack from scratch. Whether you want low-VRAM training, LoRA, QLoRA, RLHF, DPO, multi-GPU scaling, or a simple UI, there is likely a library that fits your workflow.

Here are the best open-source libraries worth knowing for fine-tuning LLMs locally. From faster speeds to reduced load, all of them have something to offer.

Table of contents

1. Unsloth

2. LLaMA-Factory

3. DeepSpeed

4. PEFT

5. Axolotl

6. TRL

7. torchtune

8. LitGPT

9. SWIFT

10. AutoTrain Advanced

Which One Should You Use?

Frequently Asked Questions

1. Unsloth

Unsloth is built for fast and memory-efficient LLM fine-tuning. It is useful when you want to train models locally, on Colab, Kaggle, or on consumer GPUs.…