Meet Notus: Enhancing Language Models with Data-Driven Fine-Tuning

In the pursuit of refining language models to align more closely with user intent and elevate response quality, a new iteration emerges – Notus. Stemming from Zephyr’s foundations, Notus, a fine-tuned version of Data Preference Optimization (DPO), emphasizes high-quality data curation for a more refined response generation process. Zephyr 7B Beta, released recently, marked a […]

The post Meet Notus: Enhancing Language Models with Data-Driven Fine-Tuning appeared first on MarkTechPost.

ai shorts applications artificial intelligence beta curation data data curation data-driven editors pick fine-tuning iteration language language models optimization process quality quality data staff stemming tech news technology zephyr