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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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12月9日 麥當勞的抵制行動非常鼓舞。 我們跟途人進行的對話和派發傳單,好奇的孩子們提出了深思熟慮的問題。 籌款根本不是我們的主要重點,但我們昨天在幾個小時也為加薩籌集了超過 1000 歐元! 🙏🏼 #Actie

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Dear people, Today 27 May we will be protesting from 1 PM- 5 PM against the bombing of Rafah! The Israeli army has bombed a displacement camp in Rafah, killing at least 35 Palestinians! The address of the protest will be: US Consolate, Museumplein 19, Amsterdam #Actie

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Today Wednesday 15/05 ‼️ 🇵🇸Nakba day decentraal sit in’s: 🔴 Amsterdam (City Hall Stopera) - 18:00 🔴 Rotterdam CS - 18:00 🔴 Den Haag CS - 17:00 🔴Utrecht CS - 18:00 🔴 Eindhoven CS - 18:00 🔴 Zwolle CS - 18:00 🔴 Leiden CS - 18:00 🔴 Zaandam CS - 18:00 🔴 Breda CS - 18:00 🔴 Den Bosch CS - 18:00 🔴 Gouda CS - 17:00 🔴 Almere CS - 18:00 🔴 Alkmaar CS - 18:00 🔴 Enschede CS - 19:00 🔴 Hilversum - 18:00 🔴 Middelburg Slavernij monument - 12:30 #actie

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