Machine_Mindset_MBTI_dataset

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.