Comment by suprjami
2 days ago
Top-K: example setting 20. Select only from the 20 most likely tokens.
Top-P: example setting 0.9. Select tokens whose probably accumulates to this number. So say you have tokens with 0.7 then 0.2 then 0.1, the last will not be selected because the first two tokens already accumulated to >=0.9.
Min-P: example setting 0.05. Don't select tokens less probable than this value. So a token with 0.1 would be considered, a token with 0.01 would not.
The purpose of all of these is to exclude very unlikely next tokens.
Min-p is specifically "Don't select tokens less probable than a multiple of the top token's probability" with min_p of 0.1 multiplied by an example top probability of 0.3 being 0.03 as the truncation at that time step.
Source: One of the min_p authors
Thanks, today I learned!