Learn how to implement automatic text summarization using deep learning in this comprehensive Python tutorial. Explore the powerful Pegasus model, built on a Transformer Encoder-Decoder architecture, for abstractive summarization of large text blocks. Follow step-by-step instructions to install dependencies, import and configure the Pegasus X-Sum model, and perform abstractive summarization on Wikipedia articles, news, and scientific journals. Gain hands-on experience with the Transformers library from Hugging Face and discover how to efficiently summarize various types of content. By the end of this tutorial, you'll have the skills to create concise summaries of lengthy texts using cutting-edge deep learning techniques.
Automatic Summarization Using Deep Learning - Abstractive Summarization With Pegasus
Overview
Syllabus
- Start
- What you'll learn
- Tutorial Kickoff
- Install Dependencies
- Load Model and Tokenizer
- Perform Abstractive Summarization on Wikipedia Articles
- Results of Summarization
- Summarizing News Articles
- Summarizing Scientific Research
Taught by
Nicholas Renotte
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