[nullc]

The VN debiaser is very simple but it's not very efficient-- it loses a lot of your randomness.

Under the same IID assumption you can take N flips that returned M heads and map them to the N choose M possible ways that could have happened. The result will (under IID assumption, even in the presence of bias) be a uniform number on the range [0..N choose M). The ctz(N choose M) trailing bits can be used directly (as they will be uniform) but the rest would have to be converted to binary via something like an arithmetic coder or rejection sampling.

The result is muuch more efficient.

Less directly, VN debiasers can also be stacked. Each debiaser outputs three streams: the normal one, one that says if the normal one output anything, and one that says if it got HH or TT. Then run VN debiasers on those. Though it takes a fairly large tree to extract most of the entropy.