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Source channel @githubtrending · Post #14993 · Jul 24

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#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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𝗗𝗜𝗔𝗥𝗜𝗢 𝗗𝗘 𝗟𝗔 𝗠𝗟𝗕 ⚾️🇺🇸

@MLB_Daily · Post #16733 · 02/11/2026, 02:02 AM

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👀 Isiah Kiner-Falefa dice que los Blue Jays estaban "contentos" de enfrentarse a los Yankees en lugar de los Red Sox en la Serie Divisional de la Liga Americana porque eran un enfrentamiento "más fácil", escribe Tim Healey del Boston Globe. 🐦 Los Jays avanzaron después de ganar la serie contra los Yankees, 3 juegos a 1. Los Yankees en la temporada regular estaban empatados con Toronto con 94 victorias, pero los Blue Jays ganaron la división a través del desempate cara a cara. Los Red Sox, que ahora tienen a IKF en su equipo, terminaron en tercer lugar con 89 victorias. #️⃣#BlueJays#IKF 🗞 | t.me/MLB_Daily

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