Axolotl Fine-Tuning Framework Docs
by Axolotl AI
Configure LLM fine-tuning entirely in YAML — the popular, reproducible way to tune open models.
Overview
Axolotl wraps the fine-tuning stack (Transformers, PEFT, DeepSpeed/FSDP, flash attention) behind a single YAML config, which makes experiments reproducible and easy to share. The docs walk through dataset formats, LoRA/QLoRA and full fine-tuning, multi-GPU training, and common recipes for popular open models. It's widely used by the open-source fine-tuning community for serious runs.
At a Glance
- Topic
- Fine-Tuning
- Level
- Advanced
- Format
- Documentation
- Cost
- Free
- Duration
- Self-paced
- Provider
- Axolotl AI
- Hands-on
- Yes — code/exercises
- Certificate
- None
What You’ll Learn
- ✓Config-driven fine-tuning via YAML
- ✓LoRA/QLoRA and full fine-tuning setups
- ✓Multi-GPU training with DeepSpeed/FSDP
- ✓Dataset formatting and reproducible recipes
Highlights
- •Reproducible, shareable YAML configs
- •Popular in the OSS fine-tuning community
Who It’s For
Best For
- ✓Teams running serious, reproducible fine-tunes
Prerequisites
- •Comfort with GPUs and the HF stack
FAQ
What is Axolotl Fine-Tuning Framework Docs?
Docs for Axolotl, a config-driven framework that streamlines fine-tuning open LLMs with LoRA/QLoRA, full fine-tuning, and more.
Is Axolotl Fine-Tuning Framework Docs free?
Axolotl Fine-Tuning Framework Docs is free to access.
What level is Axolotl Fine-Tuning Framework Docs for?
Axolotl Fine-Tuning Framework Docs is aimed at a advanced audience. Recommended background: Comfort with GPUs and the HF stack.
How long does Axolotl Fine-Tuning Framework Docs take?
Expect roughly Self-paced. Most learners work through it at their own pace.
What will I learn from Axolotl Fine-Tuning Framework Docs?
You'll learn: Config-driven fine-tuning via YAML; LoRA/QLoRA and full fine-tuning setups; Multi-GPU training with DeepSpeed/FSDP; Dataset formatting and reproducible recipes.