What would this look like?
the model generates probabilities for the next token, then you set the probability of not allowed tokens to 0 before sampling (deterministically or probabilistically)
but filtering a particular token doesn't fix it even slightly, because it's a language model and it will understand word synonyms or references.
I'm obviously talking about network output, not input.
which you can affect by just telling it to use different wording... or language for that matter
the model generates probabilities for the next token, then you set the probability of not allowed tokens to 0 before sampling (deterministically or probabilistically)
but filtering a particular token doesn't fix it even slightly, because it's a language model and it will understand word synonyms or references.
I'm obviously talking about network output, not input.
which you can affect by just telling it to use different wording... or language for that matter