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Best of Both Worlds: Fine-Tuned Small Models Complement LLMs for Cost and Performance Benefits
BERT-based models require thousands of labeled samples to train. Larger models like GPT-X require only 1-5 examples per class. However, performance, cost and time tradeoffs of such models remain under-explored. In this work, we classify survey text data into 16 classes. We focus on experimental appr
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