Welcome to the guide on performing contextual summarization using LoLLMs (Lord of Large Language Multimodal Systems). This document will walk you through the steps required to summarize documents contextually using the docs_zipper
personality.
LoLLMs is a versatile system designed to handle various tasks, including contextual summarization of documents. By leveraging the docs_zipper
personality, you can generate concise summaries that respect specific constraints such as keeping the title, author names, method, and numerical results.
docs_zipper
personality available in the personalities section.Navigate to the settings page of LoLLMs.
Under the personalities section, select the category data
and mount the docs_zipper
personality.
Add the document you want to summarize.
start
.The document will be decomposed into chunks, and each chunk will be contextually summarized. The summaries are then tied together, and the operation is repeated until the compressed text is smaller than the maximum number of tokens set in the configuration.
Here is an example of how to perform contextual summarization:
data
category and mount docs_zipper
.start
.The contextual nature of this algorithm allows for better control over the summary, ensuring that specified constraints are respected.
By following these steps, you can efficiently perform contextual summarization using LoLLMs. This method provides a high degree of control over the summary content, making it a powerful tool for document analysis.
For more detailed information, refer to the document titled "lollms_contextual_summery" located at C:\Users\aloui\Documents\content\lollms_contextual_summery.md
.
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