Introduction to Transformer Models for NLP

سرفصل های دوره

Introduction

001. Introduction to Transformer Models for NLP Introduction

Lesson 1 Introduction to Attention and Language Models

001. Topics

002. 1.1 A brief history of NLP

003. 1.2 Paying attention with attenti

004. 1.3 Encoder-decoder architectures

005. 1.4 How language models look at t

Lesson 2 How Transformers Use Attention to Process Text

001. Topics

002. 2.1 Introduction to transformers

003. 2.2 Scaled dot product attention

004. 2.3 Multi-headed attention

Lesson 3 Transfer Learning

001. Topics

002. 3.1 Introduction to Transfer Learning

003. 3.2 Introduction to PyTorch

004. 3.3 Fine-tuning transformers with PyTorch

Lesson 4 Natural Language Understanding with BERT

001. Topics

002. 4.1 Introduction to BERT

003. 4.2 Wordpiece tokenization

004. 4.3 The many embeddings of BERT

Lesson 5 Pre-training and Fine-tuning BERT

001. Topics

002. 5.1 The Masked Language Modeling Task

003. 5.2 The Next Sentence Prediction Task

004. 5.3 Fine-tuning BERT to solve NLP tasks

Lesson 6 Hands-on BERT

001. Topics

002. 6.1 Flavors of BERT

003. 6.2 BERT for sequence classification

004. 6.3 BERT for token classification

005. 6.4 BERT for questionanswering

Lesson 7 Natural Language Generation with GPT

001. Topics

002. 7.1 Introduction to the GPT family

003. 7.2 Masked multi-headed attention

004. 7.3 Pre-training GPT

005. 7.4 Few-shot learning

Lesson 8 Hands-on GPT

001. Topics

002. 8.1 GPT for style completion

003. 8.2 GPT for code dictation

Lesson 9 Further Applications of BERT + GPT

001. Topics

002. 9.1 Siamese BERT-networks for semantic searc

003. 9.2 Teaching GPT multiple tasks at once with

Lesson 10 T5 - Back to Basics

001. Topics

002. 10.1 Encoders and decoders welcome T5s architecture

003. 10.2 Cross-attention

Lesson 11 Hands-on T5

001. Topics

002. 11.1 Off the shelf results with T5

003. 11.2 Using T5 for abstractive summarization

Lesson 12 The Vision Transformer

001. Topics

002. 12.1 Introduction to the Vision Transformer (ViT)

003. 12.2 Fine-tuning an image captioning system

Lesson 13 Deploying Transformer Models

001. Topics

002. 13.1 Introduction to MLOps

003. 13.2 Sharing our models on HuggingFace

004. 13.3 Deploying a fine-tuned BERT model using Fast

Summary

001. Introduction to Transformer Models for NLP Summary

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