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Getting Started with Google BERT

You're reading from   Getting Started with Google BERT Build and train state-of-the-art natural language processing models using BERT

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781838821593
Length 352 pages
Edition 1st Edition
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Table of Contents (15) Chapters Close

Preface 1. Section 1 - Starting Off with BERT
2. A Primer on Transformers FREE CHAPTER 3. Understanding the BERT Model 4. Getting Hands-On with BERT 5. Section 2 - Exploring BERT Variants
6. BERT Variants I - ALBERT, RoBERTa, ELECTRA, and SpanBERT 7. BERT Variants II - Based on Knowledge Distillation 8. Section 3 - Applications of BERT
9. Exploring BERTSUM for Text Summarization 10. Applying BERT to Other Languages 11. Exploring Sentence and Domain-Specific BERT 12. Working with VideoBERT, BART, and More 13. Assessments 14. Other Books You May Enjoy
Exploring Sentence and Domain-Specific BERT

Sentence-BERT is one of the most interesting variants of BERT and is popularly used for computing sentence representation. We will begin the chapter by understanding how Sentence-BERT works in detail. We will explore how Sentence-BERT computes sentence representation using the Siamese and triplet network architectures. Next, we will learn about the sentence-transformers library. We will understand how to use the pre-trained Sentence-BERT model to compute sentence representation with the sentence-transformers library.

Moving on, we will understand how to make the monolingual model multilingual with knowledge distillation in detail. Next, we will learn about several interesting domain-specific BERT models, such as ClinicalBERT and BioBERT. We will learn how ClinicalBERT is trained and how it is used for predicting the probability of re...

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