Instruction Tuning

Instruction Tuning refers to the process of fine-tuning a pre-trained language model on a dataset of instructions. The goal is to make the model follow specific instructions in the input prompt. It's a way to control the behavior of the model without modifying the model architecture or retraining from scratch.

Synonyms:

IFT, Instruction Fine-Tuning

Papers published in this field over the years:

Hierarchy

Publications for Instruction Tuning

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Researchers for Instruction Tuning

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