[badsandwitch]

Has anyone tried to see what the output looks like if the model is never allowed to be uncertain?

For example, whenever certainty drops below a threshold the sampler backtracks and chooses different tokens. Such that at the end every single token had an above threshold certainty.

I doubt it would entirely eliminate undesirable outputs, but it would be interesting.

[eddd-ddde]

Couldn't that just, never get an answer?

Or maybe just says "i don't know" with full certainty.

[zbentley]

That would be extremely useful in some domains.

[Jerrrrrrry]

You used to get purely determinant near-quotes, but still affected by floating point inaccuracies.