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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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@githubtrending · Post #14792 · 06/05/2025, 01:00 PM

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#kotlin#compiler#markdown#markdown_parser#markup_language#paper#pdf#presentations#programming_language#scripting_language#slides#typesetting#typesetting_system Quarkdown is a powerful tool that helps you write and format documents using Markdown. It allows you to create complex content with functions and variables, making it more versatile than regular Markdown. You can easily compile your work into print-ready books or interactive presentations. Quarkdown supports exporting to HTML and PDF, and it includes features like live preview, which helps you see changes as you make them. This makes it easier to ensure your document looks exactly how you want it to. https://github.com/iamgio/quarkdown

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