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Introduction to Transformers for NLP - With the Hugging Face Library and Models to Solve Problems (Paperback, 1st ed.)
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Introduction to Transformers for NLP - With the Hugging Face Library and Models to Solve Problems (Paperback, 1st ed.)
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Get a hands-on introduction to Transformer architecture using the
Hugging Face library. This book explains how Transformers are
changing the AI domain, particularly in the area of natural
language processing. This book covers Transformer architecture and
its relevance in natural language processing (NLP). It starts with
an introduction to NLP and a progression of language models from
n-grams to a Transformer-based architecture. Next, it offers some
basic Transformers examples using the Google colab engine. Then, it
introduces the Hugging Face ecosystem and the different libraries
and models provided by it. Moving forward, it explains language
models such as Google BERT with some examples before providing a
deep dive into Hugging Face API using different language models to
address tasks such as sentence classification, sentiment analysis,
summarization, and text generation. After completing Introduction
to Transformers for NLP, you will understand Transformer concepts
and be able to solve problems using the Hugging Face library. What
You Will Learn Understand language models and their importance in
NLP and NLU (Natural Language Understanding) Master Transformer
architecture through practical examples Use the Hugging Face
library in Transformer-based language models Create a simple code
generator in Python based on Transformer architecture Who This Book
Is ForData Scientists and software developers interested in
developing their skills in NLP and NLU (Natural Language
Understanding)
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