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Einblick - Fine-tuning Large Language Models
Platypus: Fine-Tuned Large Language Models Achieving Top Performance
Platypus family of fine-tuned LLMs excels in performance metrics, offering efficient training and strong results.
Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning
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.
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