From my experience, abliterated models can perform worse in unexpected and subtle ways. The abliteration process also doesn’t add information that was withheld from the training set, so getting the model to answer a question that was also cleansed from its training set isn’t a recipe for producing good results.
I would recommend not using these models by default. They can be fallbacks for specific work that is triggering safeguards, but you have to monitor closely what they’re doing and if it looks reasonable or like it’s full of hallucinations.
I would recommend not using these models by default. They can be fallbacks for specific work that is triggering safeguards, but you have to monitor closely what they’re doing and if it looks reasonable or like it’s full of hallucinations.