I've been reading a bit about typical sequences (in particular from these notes (pdf alert), pages 3 and 4). Let us focus on the case of binary sequences for simplicity. As far as I understand the idea is to consider those sequences that are typical in the sense that the number of $1$s and $0$s in the sequence equals its expected number.
If the probability of a letter being $1$ is $p$, the expected number of $1$s for sequences of $n$ letters with $n\to\infty$ is $np$, and the number of such sequences is approximately equal to $$\binom{n}{np}\simeq 2^{n H(p)},\quad H(p)=-p\log_2 p-(1-p)\log_2(1-p).$$ So far, so good. The probability of a sequence being typical, that is, having $np$ $1$s, must then be $$p_t=\binom{n}{np} p^{np}(1-p)^{n(1-p)}.$$ Using Stirling I get $\log p_t\simeq0$. I guess this makes sense, as it means that in the $n\to\infty$ limit the probability of getting a typical sequence is one, hence its logarithm vanishes.
But then, where does the $p_t\simeq2^{-nH(p)}$ figure come from? Is it obtained by using the next terms in Stirling's formula, or does this require some other kind of approximation?