Text Summarization
Learn about the effective use of Llama 3 for text summarization tasks.
Text summarization is the process of converting a long piece of text into a shorter version while keeping the meaning of the original text. It helps people understand large volumes of information quickly by grasping essential details without the need to read the complete text.
Types of text summarization
There are two ways to summarize the text, i.e., extractive summarization and abstractive summarization. Let's understand how these approaches work.
Extractive summarization
This is the process of generating the summary by extracting the sentences from the original text that are important to understand its meaning. Extractive summarization only uses text from the original text without adding any rephrasing in the summary. This approach is preferable where speed and factual accuracy are concerned, as it is computationally efficient and fast.
Abstractive summarization
This is the process of generating a summary by rephrasing the original text so that it retains its meaning. However, because it involves rephrasing the text, it can sometimes lack factual accuracy. Abstractive summarization is preferable where readability and capturing the overall meaning of the text are concerned.
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