How to Build a Transformer Text Summarizer
Learn how to create a transformer-based text summarizer in Python! This step-by-step tutorial is perfect for AI learners, students, teachers, and content strategists who want to generate concise summaries from long news articles or documents.
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In this video, you’ll discover:
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How transformers predict the next word to summarize text
Preparing input sequences with articles and summaries
Using weighted cross-entropy loss to focus on summaries
Generating summaries one word at a time
A simple Python example using the 20 Newsgroups dataset
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