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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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🇿🇦Херманус — уютный городок на юго-западе ЮАР, всего в 120 км от Кейптауна. Зимой и весной сюда съезжаются туристы, чтобы наблюдать величественных южных китов 🐳. А ещё Херманус — любимое место жизни для пенсионеров, ценящих море, тишину и природу. 🏡🌅 📸 Фото и видео: https://t.me/annauar/2801 #ЮАР#Природа#Киты#Океан#Херманус#Туризм#Путешествия#ЗападныйКейп ___________________ 🇿🇦Hermanus, a charming coastal town in South Africa’s Western Cape, lies just 120 km (75 mi) from Cape Town Famous for spectacular Southern Right whale watching 🐳 during winter and spring, it’s also a beloved retirement haven. 🏡🌅 📸 Photos & Video: https://t.me/annauar/2801 #Hermanus#Whales#Whalewatching#SouthAfrica#Nature#Travel#WesternCape