Axolotl
An open-source framework for easily fine-tuning large language models with simple config files
Open-source fine-tuning framework for open-weight LLMs that wraps LoRA, QLoRA, and full-parameter training behind YAML configs, supporting multi-GPU training and dozens of model families without custom training code.
Key Features
- Supports YAML config files
- Supports LoRA and QLoRA techniques
- Supports full-parameter training
- Supports multi-GPU parallel training
- Compatible with dozens of model families
Pros
- Frees you from writing complex code
- Lowers the barrier to model fine-tuning
- Integrates many mainstream training techniques
Cons
- Requires basic command-line ability
- Requires experience assessing hardware resources
Use Cases
- Enterprises customizing domain models
- Researchers experimenting with new algorithms
- Developing a dedicated chatbot
Editor's Note
Axolotl is currently a popular top choice in the developer community for fine-tuning open-source large models.
FAQ
Which fine-tuning techniques does Axolotl support?
It supports many mainstream methods including LoRA, QLoRA, and full-parameter training.
Do I need to write code to configure it?
No. It manages training parameters and workflows entirely through YAML config files.
Does it support training on multiple GPUs at once?
Yes. Axolotl natively supports multi-GPU training to speed up model fine-tuning.
