

Advanced prompting techniques
Few-shot prompting
The basic prompts in the sections above are the examples of "zero-shot" prompts, meaning, the model has been given 
instructions and context, but no examples with solutions. LLMs that have been fine-tuned on instruction datasets, generally 
perform well on such "zero-shot" tasks. However, you may find that your task has more complexity or nuance, and, perhaps, 
you have some requirements for the output that the model doesn't catch on just from the instructions. In this case, you can 
try the technique called few-shot prompting. 
In few-shot prompting, we provide examples in the prompt giving the model more context to improve the performance. 
The examples condition the model to generate the output following the patterns in the examples.
Here's an example: 
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