Base Model: Qwen/Qwen3-4B-Instruct-2507 (Merged with initial SFT adapter)
Training Algorithm: ORPO
Objective: Improve adherence to structured output constraints (StructEval-T oriented) and suppress unrequested text/thinking processes.
Hardware: Trained on Google Colab (T4 GPU).

Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model_id = "Qwen/Qwen3-4B-Instruct-2507"
adapter_id = "daichira/qwen3-4b-structeval-orpo-v4"

tokenizer = AutoTokenizer.from_pretrained(adapter_id)
model = AutoModelForCausalLM.from_pretrained(base_model_id)
model = PeftModel.from_pretrained(model, adapter_id)