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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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@crypto_galaxy_signals · Post #171 · 01/14/2024, 08:24 PM
🌐A whopping 14.76 billion USD has been moved from an unidentified wallet to #Bitfinex. ▶️#XRP follows suit, sending nearly 50% of its market cap – a staggering 15 billion dollars – to Bitfinex. #CryptoTransfer#CryptoSignals - Crypto GALAXY
@CryptoM · Post #65032 · 04/10/2026, 02:48 PM
🚀 Significant NOM Transfer to Centralized Exchange Amid Price Drop On April 10, a substantial transfer of NOM tokens was observed. According to BlockBeats On-chain Detection, an address group holding at least 59% of NOM's circulating supply moved 23% of the tokens, totaling 674 million NOM, to a centralized exchange within the past hour. This transfer coincided with a 25% decline in NOM's price today. The address group is likely responsible for driving a sixfold increase in NOM's value over the past two weeks, from $0.0017 to $0.0126. On April 1, they withdrew 1.72 billion NOM from a centralized exchange using seven wallets, representing 59% of NOM's total circulating supply of 2.9 billion tokens. #NOM#centralizedexchange#tokentransfer#priceDrop#cryptocurrency#blockchain#onchain#crypto#cryptomarket#pricefluctuation#cryptotransfer