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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 #65371 · 04/13/2026, 02:55 AM

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🚀 BTC Decline Affects Whale's Investment Strategy On April 13, BTC experienced a slight decline, impacting the HYPE token, which fell before recovering above $41. According to BlockBeats, a major investor known for profiting from a long BTC exchange rate strategy is facing pressure, with a capital withdrawal of $1.9 million this week. The investor currently holds a BTC long position with 40x leverage, valued at $30.06 million at an average price of $70,557, and a HYPE short position with 5x leverage, valued at $23.03 million at an average price of $38.93. The positions were established during a previous HYPE surge, with the full setup completed by March 20, totaling approximately $53 million. Since the establishment of these positions, the investor has incurred a net loss of about $1.32 million, with the portfolio yet to achieve positive returns. #BTC#HYPE#WhaleInvestment#Leverage#CapitalWithdrawal#CryptoStrategy#BTCDecline#InvestmentLoss#CryptoMarket

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