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LoRA (Low-Rank Adaptation)
AI Glossary Term
What is LoRA (Low-Rank Adaptation)?
Definition
A parameter-efficient fine-tuning method that adds low-rank adapter matrices.
Related terms
Parameter-Efficient Fine-Tuning (PEFT)
Methods that adapt models by training a small subset of added parameters.
QLoRA
A fine-tuning technique that combines 4-bit weight quantization with LoRA adapters to reduce memory needs.
Fine-Tuning
Continuing training on domain-specific data to adapt a pre-trained model to a specific task.
Instruction Tuning
Fine-tuning a model on instruction-response pairs to improve task following.
DPO (Direct Preference Optimization)
A training method that fine-tunes models directly on preference pairs without needing a separate reward model.
Label Smoothing
A regularization method that softens hard labels to improve generalization.
Learn more in our free guides
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