Fine-tune Llama 2 with DPO

This article from Hugging Face likely discusses the process of fine-tuning the Llama 2 large language model using Direct Preference Optimization (DPO). DPO is a technique used to align language models with human preferences, often resulting in improved performance on tasks like instruction following and helpfulness. The article probably provides a guide or tutorial on how to implement DPO with Llama 2, potentially covering aspects like dataset preparation, model training, and evaluation. The focus would be on practical application and the benefits of using DPO for model refinement.

• •DPO is a method for aligning language models with human preferences.
• •The article likely provides a practical guide to fine-tuning Llama 2 with DPO.
• •Fine-tuning with DPO can improve model performance on various tasks.