KLD is flawed in abliteration.
I've noticed while creating my abliteration engine that KL is a flawed metric because it can be represented so many different ways, it depends completely on eval prompts, and lots of people use first token KL to make their models appear better than others. So I'm curious what do
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Technical breakdown
I've noticed while creating my abliteration engine that KL is a flawed metric because it can be represented so many different ways, it depends completely on eval prompts, and lots of people use first token KL to make their models appear better than others. So I'm curious what do you guys think is the best way to measure the difference between an abliterated model and the base. Do you guys agree or
Business impact
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