Let’s start this report by answering the obvious questions you’re likely asking:
What Is Google FLAN?
FLAN stands for Finetuned LAnguage Net, and describes a method for improving zero-shot learning for Natural Language Processing (NLP) models by using natural language instructions (instruction tuning) by making use of pretraining, finetuning and prompting.This last one is specifically interesting – and the focus of the method.Here are some important links related to this article, you may find helpful.
- The GitHub Repository: https://github.com/google-research/FLAN
Let me take an aside before we continue, and answer a question some of you make have, and an understanding of which is crucial to understanding the importance of this advancement.
What Is Zero-Shot Learning?
Zero-shot learning is a machine learning term that describes the ability of a model to to be applied to a task when it has received no training on that task, but has been trained on tasks of other types.What’s important about zero-shot for our purposes is based on the inventor, namely Google.Google search results are influenced significantly by machine learning techniques concentrated mainly in the NLP space. The ability to move learnings from one task to another to speed up the progress in that new task is highly significant.More on this below.
What About Pre-Training, Fine-Tuning and Prompting?
Some other core concepts that will be helpful to understand before we proceed are:
- Pre-Training: Like humans,...
Read Full Story: https://beanstalkim.com/learn/seo/google-bakes-a-flan-improved-zero-shot-learning-for-nlp/
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