Another way to put the model into no-mans-land, and have it return random neural knowledge is to exploit the repetition penalty. It can’t make that token again and has no other context. Temperature 0:
One of the settings that really seems important is to set Top_P = 1. If you don’t do this, it won’t ramble.
I have tried increasing either the frequency penalty, or the presence penalty (or both) and doing so forces the AI to pick new tokens each time, and it results in gibberish. So, I guess, “sometimes you need to repeat yourself” in order to make sense.
So, final settings:
Temperature = 2 (for max hallucination)
Top P = 1 (important for max response length)
Presence Penalty = 0 (to prevent generating total gibberish)
Frequency Penalty = 0 (to prevent generating total gibberish)
That was GPT-3.5. GPT-4 has multiple token generating engines and logit probability checkers to keep it on track. One of the best selected paths by the mixture might be the one that says “I don’t know what you’re saying”.