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LLMs have default personalities - shaped by RLHF and other post-training methods. There is a lot of variance to it, but variance from one LLM to another is much higher than that within the same LLM.

If you want an LLM to retain the same default personality, you pretty much have to use an open weights model. That's the only way to be sure it wouldn't be deprecated or updated without your knowledge.

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I'd argue that's "underlying hidden authorial style" as opposed to what most people mean when they refer to the "personality" of the thing they were "chatting with."

Consider the implementation: There's document with "User: Open the pod bay doors, HAL" followed by an incomplete "HAL-9000: ", and the LLM is spun up to suggest what would "fit" to round out the document. Non-LLM code parses out HAL-9000's line and "performs" it at you across an internet connection.

Whatever answer you get, that "personality" is mostly from how the document(s) described HAL-9000 and similar characters, as opposed to a self-insert by the ego-less name-less algorithm that makes documents longer.

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