PEFT (Parameter-Efficient Fine-Tuning)
llm library
Hugging Face library for efficient fine-tuning
Supported languages
PEFT is Hugging Face's official library for parameter-efficient fine-tuning techniques. It implements methods like LoRA, QLoRA, Prefix Tuning, and more, allowing adaptation of large models with minimal resources.
Concepts
loraqloraprefix-tuningprompt-tuningadapter-modulesia3adalora
Pros and Cons
Ventajas
- + Official LoRA/QLoRA implementations
- + Seamless Transformers integration
- + Multiple PEFT methods available
- + Excellent documentation
- + Very active community
- + Frequent updates
Desventajas
- - Python only
- - Learning curve for advanced methods
- - Some techniques are experimental
- - Dependent on HF ecosystem
Casos de Uso
- LLM fine-tuning with limited GPU
- Creating specialized adapters
- Experimenting with different PEFT methods
- Production of adapted models
- Research in efficient fine-tuning