'Understanding the get_prior output in brms package

I'm relatively new to Bayesian modeling in R and am trying to understand how to interpret the get_prior output and how to use the information in the set_prior function. I have the output below.

> get_prior(ILICount~Occupants + Population, data = analysisworksheet, family = poisson())
              prior     class       coef group resp dpar nlpar lb ub       source
             (flat)         b                                             default
             (flat)         b  Occupants                             (vectorized)
             (flat)         b Population                             (vectorized)
student_t(3, 5.2, 2.5) Intercept                                          default
Warning message:
Rows containing NAs were excluded from the model.

r modeling bayesian poisson

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'Understanding the get_prior output in brms package

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