Junior interview questionAsked at Lyft · interview write-up
What is the difference between a transformer and an embedding model, and between pretraining and fine-tuning?
Model answer
A transformer is an architecture. An embedding model is usually a transformer encoder trained to turn a text into one vector, so similar texts sit close; a generative one predicts the next token. Pretraining learns general language from unlabeled text; fine-tuning adapts those weights to a task with a smaller, targeted dataset.
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