Machine_Mindset_MBTI_dataset

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## Dataset introduction There are four dimension in MBTI. And there are two opposite attributes within each dimension. To be specific: + Energe: Extraversion (E) - Introversion (I) + Information: Sensing (S) - Intuition (N) + Decision: Thinking (T) - Feeling (F) + Execution: Judging (J) - Perceiving (P) Based on the above, you can infer the content of the json file from its name. The datasets follow the Alpaca format, consisting of instruction, input and output. ## How to use these datasets for behavior supervised fine-tuning (SFT) For example, if you want to make an LLM behave like an *ISFJ*, you need to select *the four corresponding files* (en_energe_introversion.json, en_information_sensing.json, en_decision_feeling.json, en_execution_judging.json). And use the four for SFT. ## How to use these datasets for direct preference optimization (DPO) For example, if you want to make an LLM be *more feeling (F) than thinking (T)* by DPO, you need to select *the two corresponding files* (en_decision_feeling.json, en_decision_thinking.json). And then compile the two into the correct format for DPO. For the correct format, please refer to this.