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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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Google Facts™ [ ️@googlefactss🌎]

@googlefactss · Post #40717 · 03/01/2026, 07:02 AM

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Georgy Zhukov was a Soviet military leader and Marshal of the Soviet Union. He was born to a poor peasant family in Strelkovka, Kaluga Province, Russia. He served in the Imperial Russian Army in World War I. After the Russian Revolution, he joined the Red Army and rose quickly through the ranks. He commanded Soviet forces at major battles, including Khalkhin Gol, Moscow, Stalingrad, Kursk, and the final assault on Berlin. He became Marshal of the Soviet Union in January 1943. After World War II, he was the first military governor of the Soviet occupation zone in Germany. He later served as Chief of the General Staff and Minister of Defence. He was removed from top posts because Soviet political leaders feared his popularity and power. Zhukov is remembered as one of the most celebrated Soviet commanders of the 20th century. 🪖⚔️🇷🇺 [Read more] @googlefactss #GeorgyZhukov#SovietUnion#WorldWarII#Marshal#MilitaryHistory#EasternFront

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