Attention is all you need || Transformers Explained || Quick Explained

Developers Hutt · Beginner ·🧬 Deep Learning ·4y ago

About this lesson

Attention is all you need paper dominated the field of Natural Language Processing and Text Generation forever. Whether you think about GPT3, BERT, or Blenderbot, the state-of-the-art models or the NLP systems are around us use Transformers. So here I explained the backbone of Transformers (Attention Head) as fast as possible. I hope you'll like it. Your feedback means a lot to me. So please try to leave one. And as always, Thanks for watching. For query or updates, stay tuned with Instagram Instagram: https://www.instagram.com/developershutt Timestamps: 0:00 Introduction 0:43 Limits of RNNs 2:07 Intro to self-attention 3:30 Positional Encoding 5:15 Multi-Head Attention 7:23 Decoder 9:46 Masked Multi-Head Attention 10:49 Things to remember

Original Description

Attention is all you need paper dominated the field of Natural Language Processing and Text Generation forever. Whether you think about GPT3, BERT, or Blenderbot, the state-of-the-art models or the NLP systems are around us use Transformers. So here I explained the backbone of Transformers (Attention Head) as fast as possible. I hope you'll like it. Your feedback means a lot to me. So please try to leave one. And as always, Thanks for watching. For query or updates, stay tuned with Instagram Instagram: https://www.instagram.com/developershutt Timestamps: 0:00 Introduction 0:43 Limits of RNNs 2:07 Intro to self-attention 3:30 Positional Encoding 5:15 Multi-Head Attention 7:23 Decoder 9:46 Masked Multi-Head Attention 10:49 Things to remember

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Chapters (8)

Introduction

0:43 Limits of RNNs

2:07 Intro to self-attention

3:30 Positional Encoding

5:15 Multi-Head Attention

7:23 Decoder

9:46 Masked Multi-Head Attention

10:49 Things to remember

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