There is a difference in the labelling of the initial seasonal states. Of course only the free estimated ones are reported by tidy() but it may be better to have consistent labels between the two.

May be sticking with l0, b0, s0, s1, s2, s3 would be best.

aus_holidays <- tourism %>%
filter(Purpose == "Holiday") %>%
summarise(Trips = sum(Trips))
fit <- aus_holidays %>%
model(ETS(Trips))
report(fit)
report(fit)

Series: Trips
Model: ETS(M,N,M)
Smoothing parameters:
alpha = 0.3578226
gamma = 0.0009685565

Initial states:
l s1 s2 s3 s4
9666.501 0.9430367 0.9268433 0.968352 1.161768

sigma^2: 0.0022

 AIC     AICc      BIC

1331.372 1332.928 1348.046

tidy(fit)

A tibble: 6 x 3

.model term estimate

1 ETS(Trips) alpha 0.358
2 ETS(Trips) gamma 0.000969
3 ETS(Trips) l 9667.
4 ETS(Trips) s0 0.943
5 ETS(Trips) s1 0.927
6 ETS(Trips) s2 0.968