Category:
Category:
Task-specific Adapters (LoRA / PEFT)
Category:
Model Training & Optimization
Definition
Small modular parameters that allow models to specialize without fully retraining.
Explanation
Adapters such as LoRA or PEFT enable fine-tuning small sections of a model while keeping the base weights frozen. This dramatically reduces the cost and compute requirements of domain or task adaptation. Adapters can be combined, stacked, or swapped, making them ideal for multi-domain enterprises.
Technical Architecture
Base Model → Adapter Layer (LoRA/PEFT) → Fine-Tuning → Specialized Model
Core Component
Adapter modules, low-rank matrices, training pipeline
Use Cases
Domain adaptation, personalization, multi-tenant enterprise AI
Pitfalls
Adapter conflicts; version explosion; poor transferability
LLM Keywords
Lora, Peft, Adapters, Model Fine Tuning
Related Concepts
Related Frameworks
• Fine-Tuning
• Domain Adaptation
• Distillation
• Adapter Architecture Map