Zero-Shot V.S. Few-Shot Prompting

If you can describe what you want to the model, you can use zero-shot prompting for example

Classify the text into positive, neutral or negative:
Text: That shot selection was awesome.
Classification:

The model response: Positive, this is because the model can understand “awesome” is a positive sensation.

If you can't describe, then you can use few-shot prompting by showing some examples to the model to let it learn and response, for example

Text: Today the weather is fantastic
Classification: Pos
Text: The furniture is small.
Classification: Neu
Text: I don't like your attitude
Classification: Neg
Text: That shot selection was awful
Classification:

Then the model response: Neg. The model response this instead of Negative since it is what is provided in the examples.

Reference: here