For 1B to 3B models, prompting alone is near random, while training a small classification head on frozen weights is the most accurate and VRAM-efficient path, with data volume and pretraining domain as the main bottlenecks.
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Small Language Models in the Real World: Insights from Industrial Text Classification
For 1B to 3B models, prompting alone is near random, while training a small classification head on frozen weights is the most accurate and VRAM-efficient path, with data volume and pretraining domain as the main bottlenecks.