# Preference Learning

URM-LLaMa-3.1-8B is an uncertainty-aware reward model designed to enhance the alignment of large language models.

SimPO is a simple preference optimization method that eliminates the need for reference rewards, aiming to enhance model performance by simplifying the preference optimization process.

AmberSafe is a safety fine-tuned instruction model based on LLM360/AmberChat, belonging to the LLM360 Pebble series, focusing on providing secure text generation capabilities.