CNCL-Penn-State/MuCE
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How to use CNCL-Penn-State/CrPO-RM-gemma-2-9b-it with PEFT:
from peft import PeftModel
from transformers import AutoModelForSequenceClassification
base_model = AutoModelForSequenceClassification.from_pretrained("google/gemma-2-9b-it")
model = PeftModel.from_pretrained(base_model, "CNCL-Penn-State/CrPO-RM-gemma-2-9b-it")This is the reward model (gemma-2-9b-it model finetuned on the MuCE dataset) used to measure the quality of model generations in the Creative Preference Optimization paper.
@misc{ismayilzada2025creativepreferenceoptimization,
title={Creative Preference Optimization},
author={Mete Ismayilzada and Antonio Laverghetta Jr. and Simone A. Luchini and Reet Patel and Antoine Bosselut and Lonneke van der Plas and Roger E. Beaty},
year={2025},
eprint={2505.14442},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2505.14442},
}