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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 M - Crypto News

@CryptoM · Post #65443 · 04/13/2026, 09:04 AM

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🚀 Investor Shifts Focus from Oil to U.S. Stock Market On April 13, Hyperinsight reported that the largest holder of short positions in crude oil on Hyperliquid, identified as address 0xa65, closed their loss-making positions last week and briefly attempted to go long in an effort to capitalize on a market bottom. According to BlockBeats On-chain Detection, the investor subsequently closed these positions and exited the oil market entirely. The investor has now shifted their focus to the U.S. stock market, specifically the storage sector. They have retained two long positions opened earlier this month in Micron Technology (MU) and SanDisk (SNDK), with a total holding size of $5.4 million. The current floating profit from these positions has reached $1.15 million. #Investor#OilMarket#USStockMarket#MicronTechnology#SanDisk#Investing#StockMarket#Finance#MarketShift#Hyperliquid#BlockBeats

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