For those wondering how it works:
> The language model predicts the probabilities of the next token. An arithmetic coder then encodes the next token according to the probabilities. [1]
It’s also mentioned that the model is configured to be deterministic, which is how I would guess the decompression is able to map a set of token likelihoods to the original token?