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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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Yu’s Life

@pseudoyulife · Post #3588 · 01/10/2025, 01:57 AM

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🎮 最近在玩双人成行 It Takes Two #douban#playing http://www.douban.com/game/35110438/

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Tomoko RD

@tomoko_channel · Post #696 · 10/07/2024, 03:19 PM

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🎮 最近在玩兰斯10：决战 Rance X -決戦- #playing#douban 评分: ★★★★★ 标签: 神作 GAL 卡牌 Alicesoft 兰斯 备注: 鉴定为 Roguelite，Bad End 了 3 次之后，拿着别人的高 CP 存档重开了，慢慢品尝。（根本停不下来） http://www.douban.com/game/27149415/

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