It doesn’t work like that. The LLM has no way to be “aware” of its own sampling and tokenization, and it can’t choose what token the sampler ends up picking.
You can give it a list of “banned words” or preferred words that match up to tokens in the prompts to skew it some, I suppose, but that would be a really long list. And one would need the dictionary as a “key.”
It doesn’t work like that. The LLM has no way to be “aware” of its own sampling and tokenization, and it can’t choose what token the sampler ends up picking.
You can give it a list of “banned words” or preferred words that match up to tokens in the prompts to skew it some, I suppose, but that would be a really long list.
It doesn’t work like that. The LLM has no way to be “aware” of its own sampling and tokenization, and it can’t choose what token the sampler ends up picking.
You can give it a list of “banned words” that match up to tokens in the prompts to skew it some, I suppose.
It doesn’t work like that. The LLM has no way to be aware of its own sampling and tokenization, and it can’t “choose” what token the sampler ends up picking.
You can give it a list of “banned words” that match up to tokens in the prompts to skew it some, I suppose.