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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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@amazingeo · Post #630 · 02/13/2026, 08:31 PM
🌍 Tokyo’s Shinjuku train station is the world’s busiest, with over 3.5 million passengers passing through daily. Its vast underground networks are so complex that some exits are kilometers apart. ✨ #urbanization⚡#infrastructure⚡#transit⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography 👉more Channels
@amazingeo · Post #87 · 08/21/2025, 03:12 AM
🌍 Tokyo’s rail system is so efficient that over 13 billion train trips are made each year within the city. This high-capacity network helps keep the world’s largest metropolitan area moving smoothly. ✨ #Tokyo⚡#transit⚡#urban⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography🌍
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