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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.
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
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.
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
Explains how to create Hugging Face applications for NLP tasks like sentiment analysis and sentence masking
Covers code generator examples using Transformers
Explains the language models such as Google BERT, Open AI GPT2, and other open-source models with examples
Erscheinungsjahr: | 2022 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
xi
165 S. 80 s/w Illustr. 165 p. 80 illus. |
ISBN-13: | 9781484288436 |
ISBN-10: | 1484288432 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Jain, Shashank Mohan |
Auflage: | 1st ed. |
Hersteller: |
Apress
Apress L.P. |
Maße: | 235 x 155 x 11 mm |
Von/Mit: | Shashank Mohan Jain |
Erscheinungsdatum: | 21.10.2022 |
Gewicht: | 0,283 kg |
Explains how to create Hugging Face applications for NLP tasks like sentiment analysis and sentence masking
Covers code generator examples using Transformers
Explains the language models such as Google BERT, Open AI GPT2, and other open-source models with examples
Erscheinungsjahr: | 2022 |
---|---|
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: |
xi
165 S. 80 s/w Illustr. 165 p. 80 illus. |
ISBN-13: | 9781484288436 |
ISBN-10: | 1484288432 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: | Jain, Shashank Mohan |
Auflage: | 1st ed. |
Hersteller: |
Apress
Apress L.P. |
Maße: | 235 x 155 x 11 mm |
Von/Mit: | Shashank Mohan Jain |
Erscheinungsdatum: | 21.10.2022 |
Gewicht: | 0,283 kg |