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Chain-of-Thought Prompting: Making LLMs Reason
Chain-of-thought prompting asks a model to write out its reasoning before the answer. This guide explains why that helps, measures it on 20 arithmetic word problems with a small open model, counts what the extra tokens cost, and explains why newer reasoning models have made the instruction unnecessary for them.
Few-Shot vs Zero-Shot Prompting: A Practical Guide
Few-shot prompting means showing a model examples before asking it to do the task. The usual advice is that examples help. This guide tests that on 48 real customer messages with a small open model, and finds a case where more examples made results worse and one-line definitions worked better than any of them.