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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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电竞-体育-LPL LCK俱乐部消息-中文频道推荐群

@dianjingtiyuxieyi · Post #5657 · 09/06/2025, 02:23 PM

刀塔-TI国际邀请赛 #BOOM 对战 Wildcard (BO3) 2025-09-06 19:00 第三局获胜: BOOM 第三局击杀让分:BOOM -11.5 第三局击杀大小: 小于42.5 (重心) 第三局时间大小: 小于39 第一滴血: BOOM

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@dianjingtiyuxieyi · Post #5655 · 09/06/2025, 12:46 PM

刀塔-TI国际邀请赛 #BOOM 对战 Wildcard (BO3) 2025-09-06 19:00 第二局获胜: BOOM 第二局击杀让分:BOOM -11.5 (重心) 第二局击杀大小: 大于41.5 第二局时间大小: 小于38 第一滴血: BOOM

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@dianjingtiyuxieyi · Post #5647 · 09/06/2025, 11:15 AM

刀塔-TI国际邀请赛 #BOOM 对战 Wildcard (BO3) 2025-09-06 19:00 第一局获胜: BOOM 第一局击杀让分:BOOM -9.5 第一局击杀大小: 小于44.5 (重心) 第一局时间大小: 小于39 第一滴血: BOOM

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@dianjingtiyuxieyi · Post #5627 · 09/05/2025, 05:35 PM

刀塔-TI国际邀请赛 #BOOM 对战 Nemesis (BO3) 2025-09-05 22:00 第二局获胜:Nemesis 第二局击杀让分:Nemesis+6.5 第二局击杀大小:小于43.5 (重心) 第二局时间大小:小于40 第一滴血:BOOM

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@dianjingtiyuxieyi · Post #5617 · 09/05/2025, 04:39 PM

刀塔-TI国际邀请赛 #BOOM 对战 Nemesis (BO3) 2025-09-05 22:00 第一局获胜:BOOM 第一局击杀让分:BOOM-3.5 第一局击杀大小:小于44.5 第一局时间大小:小于41 (重心) 第一滴血:BOOM

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Mountstorm notes

@mountstorm · Post #238 · 06/15/2022, 08:23 AM

#boom I guess, it is good for the first time) 😋 Next time I do my best to 7.0 + 💪 📅 12.06.2022 Mock exam - Band 6.5

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