This repository hosts a fine-tuned version of google/flan-t5-base, adapted for generating random, personality-themed questions in the context of the Myers–Briggs Type Indicator (MBTI) framework.

The model produces short, standalone prompts designed to encourage self-reflection and discussion related to personality traits, emotions, and decision-making.
It operates as a randomized question generator rather than an interactive conversational model.

Model Purpose

The goal of this model is to generate concise, psychologically relevant questions similar to those found in MBTI-style interviews or self-assessment forms.
Each output question is intended to provoke reflection or reveal an aspect of human cognition, motivation, or behavior.

Key Characteristics:

Generates independent questions — no memory or contextual carryover between generations.
Optimized for single-turn usage (no long-term dialogue support).
Produces diverse questions across multiple MBTI domains (e.g., intuition, sensing, thinking, feeling, judging, perceiving).
Ideal for personality research tools, psychological chatbots, or training datasets for reflective AI dialogue.

Example Usage

python

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model = AutoModelForSeq2SeqLM.from_pretrained("f3nsmart/ft-flan-t5-base-qgen")
tokenizer = AutoTokenizer.from_pretrained("f3nsmart/ft-flan-t5-base-qgen")

prompt = "Generate a question about emotional decision-making."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=60)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

sadovsky/ft-flan-t5-base-qgen_v2

Flan-T5 Base — MBTI Random Question Generator

Model Purpose

Example Usage

sadovsky/
ft-flan-t5-base-qgen_v2