K1mG0ng/AI-taste-ob-4B

AI-Taste-OB-4B

This repository provides a fine-tuned Qwen3 4B model for AI Taste experiments on social science research articles, with a current focus on organizational behavior style article evaluation.

Model Summary

• —Base model: Qwen/Qwen3-4B
• —Architecture: Qwen3ForCausalLM
• —Format: Hugging Face Transformers + Safetensors
• —Primary use: ranking or classifying research-article prompts into discrete quality levels

Intended Use

The model is intended for research and internal experimentation on structured article-evaluation prompts, including tasks such as:

• —research question quality assessment
• —article-level prompt scoring
• —social science taste benchmarking

It is not intended as a general-purpose factual assistant or as a substitute for expert peer review.

Files

This repository keeps only the files needed to load and run the model:

• —model weights in safetensors
• —tokenizer files
• —model config and generation config

Training-state artifacts such as trainer checkpoints and local run metadata are intentionally excluded.

Example

from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "K1mG0ng/AI-taste-ob-4B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

Notes

• —This is a fine-tuned research model.
• —Output quality depends on prompt format and label schema used at inference time.
• —Benchmark datasets and training framework are maintained separately.