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.

Tutorial: Curate an instruction dataset for supervised fine-tuning

Supervised Fine Tuning

Hyperparameters used for fine-tuning BASE- size models on XNLI and

Your ChatGPT Questions Answered

Fine-Tune XLSR-Wav2Vec2 for low-resource ASR with 🤗 Transformers

Supervised TCR repertoire classification a Multiple-Instance

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

LLM Sleeper Agents — Klu

Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)