What is supervised fine-tuning? — Klu

Supervised fine-tuning (SFT) is a method used in machine learning to improve the performance of a pre-trained model. The model is initially trained on a large dataset, then fine-tuned on a smaller, specific dataset. This allows the model to maintain the general knowledge learned from the large dataset while adapting to the specific characteristics of the smaller dataset.

Lecture 8: How ChatGPT Works Part 1 - Supervised Fine-Tuning

CoFRIDA: Self-Supervised Fine-Tuning for Human-Robot Co-Painting

Fine-Tuning In A Nutshell - FourWeekMBA

What is Zephyr 7B? — Klu

Understanding and Using Supervised Fine-Tuning (SFT) for Language

Understanding and Using Supervised Fine-Tuning (SFT) for Language

Supervised Fine-tuning: customizing LLMs

Understanding and Using Supervised Fine-Tuning (SFT) for Language

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