It's possible to deterministically sample from a probability distribution. For example, just seed your RNG with a constant, or with the SHA256 hash of the context.
It's possible to deterministically sample from a probability distribution. For example, just seed your RNG with a constant, or with the SHA256 hash of the context.
Well yes, you can "hack" the pseudorandom number generator, but... that's not really the point when talking about determinism in LLMs is it? I mean the mathematical idea of the standard LLM is certainly truly random.
> I mean the mathematical idea of the standard LLM is certainly truly random.
Not really, LLMs give you a distribution over possible next tokens. You are free to then sample from this distribution how you want. There is no need to hack RNG or whatever, for example you can simply just take a greedy approach and always output the most likely token, in which case the LLM becomes deterministic (mathematically). This is equivalent to setting the temperature to 0.