How to audit preference biases and fine-tune with DPO (TRL + LoRA)

Tutorial walks through an end-to-end preference-learning workflow on the Anthropic HH-RLHF dataset: loading and parsing chosen–rejected pairs in Colab, auditing the data for structural and preference biases, then fine-tuning with Direct Preference Optimization using TRL and LoRA.