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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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Coin Sonar

@CoinSonar · Post #244204 · 04/18/2026, 01:22 PM

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Coin Sonar

@CoinSonar · Post #244138 · 04/18/2026, 11:06 AM

#PNUT | Volume spike (USDT PAIR) 9 times the average volume 136.77K USDT traded in 15 min └Selling vol: 89.82K USDT 🔴 Boost score: 1/10 24h Vol: 1.34M USDT (Binance) Price: 0.0611 (-3.7% in 24h)

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@CoinSonar · Post #244002 · 04/18/2026, 06:01 AM

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@CoinSonar · Post #243954 · 04/18/2026, 04:01 AM

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@CoinSonar · Post #243919 · 04/18/2026, 02:01 AM

#PNUT | Volume spike (USDT PAIR) 9 times the average volume 138.12K USDT traded in 15 min └Selling vol: 78.16K USDT 🔴 Boost score: 1/10 24h Vol: 1.34M USDT (Binance) Price: 0.0680 (-3.7% in 24h)

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