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If you run these on your own hardware can you take the guard-rails off (ie "I'm afraid I can't assist with that"), or are they baked into the model?
even chat gpt will help you crack them if you ask it nicely
If you run these on your own hardware can you take the guard-rails off (ie "I'm afraid I can't assist with that"), or are they baked into the model?
LLM noob here. Would this optimization work with any MoE model or is it specific for this one?
It worked with Qwen 3 for me, for example.
The option is just a shortcut, you can provide your own regex to move specific layers to specific devices.
If you run these on your own hardware can you take the guard-rails off (ie "I'm afraid I can't assist with that"), or are they baked into the model?
You need to find an abliterated finetune, where someone sends prompts that would hit the guardrails, traces the activated neurons, finds the pathway that leads to refusal, and deletes it.
Earlier quoted context omitted.
You need to find an abliterated finetune, where someone sends prompts that would hit the guardrails, traces the activated neurons, finds the pathway that leads to refusal, and deletes it.
I've been hearing that in this case, there might not be anything underneath- that somehow OpenAI managed to train on exclusively sterilized synthetic data or something.
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Your comment will get donvoted to invisibility anyways (or mayhaps even flagged), but I have to ask: what are you trying to accomplish with comments such this? Just shitting at it because it isnt as good as youd like yet? You want the best of tomorrow today, and will only be rambling about how its not good enough yesterday?
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