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Source channel @githubtrending · Post #14993 · Jul 24

#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch

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@CoinSonar · Post #243681 · 04/17/2026, 01:29 PM

#SOL | Volume spike (BTC PAIR) 70 times the average volume 8.431 BTC traded in 1 min └Selling vol: 5.858 BTC 🔴 Boost score: 1/10 24h Vol: 172.656 BTC (Binance) Price: 0.0011659 (-2.1% in 24h)

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Coin Sonar

@CoinSonar · Post #243680 · 04/17/2026, 01:29 PM

#SOL | Volume spike (USDT PAIR) 59 times the average volume 10.41M USDT traded in 1 min └Buying vol: 7.71M USDT 🟢 Boost score: 5/10 24h Vol: 250.59M USDT (Binance) Price: 89.52 (-3.6% in 24h)

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@CoinSonar · Post #243284 · 04/16/2026, 07:08 PM

#SOL | Volume spike (BTC PAIR) 188 times the average volume 22.542 BTC traded in 1 min └Selling vol: 19.917 BTC 🔴 Boost score: 1/10 24h Vol: 172.656 BTC (Binance) Price: 0.0011880 (-2.1% in 24h)

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