ft-flan-t5-base-qgen_v2

Flan-T5 Base — MBTI Random Question Generator

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.

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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.

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Example Usage

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))