i got banned and they refused to tell me why after multiple support tickets. this was > 1y ago. i definitely didn't do anything wrong (i wasn't even using it) so it was either a compromised key or they make mistakes. playing with prompts could potentially get you swept up into some nonsense like that.
I'm not sure if I'm misunderstanding you or the article, but as far as I understand it from a cursory reading this is not a jailbreak. They use this one prompt for fine tuning and use the model's response to the prompt as the sole underlying benchmark.
How would you do this with a closed weights model?
That's pretty interesting. It was already well-known that you could easily remove safety training from open-weights models by a bit of finetuning, but apparently you don't even need a finetuning dataset, as long as you have just a few prompts and another LLM to judge responses? Let's see if the abliteration people take a note of this.
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They only tested it on open weight models. I wonder if it also works on the closed ones, bit I don't really want to get banned
not to discourage anyone, just saying.
How would you do this with a closed weights model?