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Text Summarization with Google AI's T5 in Python
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Easy text summarization using Google AI's T5 model using HuggingFace transformers and PyTorch in Python.
Automatic text summarization allows us to shorten long pieces of text into easy-to-read, short snippets that still convey the most important and relevant information of the original text.
In this video, we’ll build a simple but incredibly powerful text summarizer using Google’s T5. We’ll be using the PyTorch and HuggingFace’s Transformers frameworks.
This is split into three parts:
1. Import and Initialization
2. Data and Tokenization
3. Summary Generation
🤖 70% Discount on the NLP With Transformers in Python course:
You can read the article version of this on Medium here:
(And for those of you without Medium membership, here's a free link):
Thumbnail background by gustavo centurion on Unsplash
Automatic text summarization allows us to shorten long pieces of text into easy-to-read, short snippets that still convey the most important and relevant information of the original text.
In this video, we’ll build a simple but incredibly powerful text summarizer using Google’s T5. We’ll be using the PyTorch and HuggingFace’s Transformers frameworks.
This is split into three parts:
1. Import and Initialization
2. Data and Tokenization
3. Summary Generation
🤖 70% Discount on the NLP With Transformers in Python course:
You can read the article version of this on Medium here:
(And for those of you without Medium membership, here's a free link):
Thumbnail background by gustavo centurion on Unsplash
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