Model Training
LoRA (Low-Rank Adaptation)
A clever shortcut for fine-tuning AI models, adjusting only a tiny fraction of the weights to save time and money.
Definition
A parameter-efficient fine-tuning technique that adds small, trainable low-rank matrices to existing model layers instead of updating all weights. Reduces training compute and memory by 90%+.
Why it matters
Made fine-tuning foundation models accessible to companies without massive GPU budgets.
Related terms in Model Training
Adversarial Training
Teaching an AI to defend itself by constantly attacking it with tricky or malicious inputs during training.
Autoencoders
A neural network that learns to compress data into a small code and then unzip it back to the original.
Distillation (Model Distillation)
Teaching a small, fast AI model to mimic a large, expensive one, so you get similar results at a fraction of the cost.
Dropout
Randomly turning off some neurons during training so the AI doesn't over-memorize and can generalize better.
From vocabulary to outcomes
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