What it does
Fine-tuning means further training an existing AI model on your own data so it gets better at a specific job. Doing this for a whole large model takes a lot of computer power. PEFT (Parameter-Efficient Fine-Tuning) instead trains a small set of extra settings, often well under one percent of the model's size, while leaving the rest untouched.
This cuts the memory and storage needed, so models can be adapted on far more modest hardware, and the trained add-on (popular methods include LoRA) is a small file. Its makers say results can come close to fully fine-tuned models.
It works with Hugging Face's other libraries for text, image-generation and large-scale training.
Who it's for
Developers and researchers who want to customise AI models without huge computing budgets.
Can I use it without coding?
Developers only. It's a Python library; you write code to use it, and training needs a graphics card. New to this? Start here.
Can I run it?
- Cost
- FreeNothing to pay or sign up for.
- Computer
- Works best on a powerful computer or one with a graphics card (GPU)
- API key
- Not needed
Try it
Using Claude Code, Cursor or another AI coding assistant? Paste the prompt and it will walk you through the setup.New to this?
Before you install
- Only download from the official GitHub page. Copies with similar names exist for many popular projects.
- License (Apache-2.0): Permissive: free to use, change and share, including for business.
- More on staying safe