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4 results for “fine-tuning”
Fine-Tuning
The process of further training a pre-trained machine learning model on a smaller, task-specific dataset to adapt its weights for a particular domain, task, or desired behaviour.
LoRA (Low-Rank Adaptation)
LoRA is a parameter-efficient fine-tuning technique that adapts large pre-trained models by injecting small trainable low-rank matrices into transformer layers, drastically reducing the number of trainable parameters without sacrificing performance.
Parameter-Efficient Fine-Tuning
A family of techniques that adapts a pretrained language or vision model to a downstream task by training only a small fraction of its parameters, dramatically reducing compute, memory, and storage requirements compared to full fine-tuning.
Transfer Learning
Transfer learning is a machine learning technique in which a model pre-trained on one task or dataset is adapted for a different but related task, enabling high performance with significantly less data and compute than training from scratch.