
The author argues that incorporating reasoning processes during fine-tuning of Large Language Models can enhance model robustness and overcome overfitting, even without directly outputting reasoning processes during deployment.


coremsg

adapting-large-language-models-for-content-moderation-pitfalls-in-data-engineering-and-supervised-fine-tuning


Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning


title_rewrite


Platypus family of fine-tuned LLMs excels in performance metrics, offering efficient training and strong results.


platypus-fine-tuned-large-language-models-achieving-top-performance


Platypus: Fine-Tuned Large Language Models Achieving Top Performance
