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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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@PinYunPs · Post #15273 · 02/03/2025, 10:49 AM

#Mickey 官网: https://tech.mickey.business 频道: @mickey233333 群组: @mickey2333

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📱 𝐃𝐍𝐙 𝐓𝐄𝐌𝐀𝐒 🔠🔠 >> 🔠🔠🔠 📱 📢 𝗖𝗵𝗮𝗻𝗻𝗲𝗹: @DNZ_Temas #Mickey#dark ➖ ➖ ➖ ➖ ➖ ➖ ➖ ➖ ➖ ➖ ➖ ➖ ⚠️𝐀𝐏𝐏𝐋𝐘 𝐓𝐇𝐄𝐌𝐄 📱 ( Telegram ) ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ ➡️𝗕‌𝐀𝐂𝐊𝐆𝐑𝐎𝐔𝐍𝐃 ➖➖➖➖➖➖➖➖ 🖼𝐖𝐀𝐋𝐋𝐏𝐀𝐏𝐄𝐑 ➖➖➖➖➖➖➖ ⠀ ╚════ ღ 𝔻ℕℤ 𝕋𝔼𝕄𝔸𝕊 ღ ══╝

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📱 𝐃𝐍𝐙 𝐓𝐄𝐌𝐀𝐒 🔠🔠 >> 🔠🔠🔠📱 📢 𝗖𝗵𝗮𝗻𝗻𝗲𝗹: @DNZ_Temas🇧🇷 #Mickey#green ➖➖➖➖➖➖➖➖➖➖➖➖ ⚠️𝐀𝐏𝐏𝐋𝐘 𝐓𝐇𝐄𝐌𝐄📱 ( Telegram ) ➖➖➖➖➖➖➖➖➖➖➖➖➖➖➖ ➡️𝗕‌𝐀𝐂𝐊𝐆𝐑𝐎𝐔𝐍𝐃 ➖➖➖➖➖➖➖➖ 🖼𝐖𝐀𝐋𝐋𝐏𝐀𝐏𝐄𝐑 ➖➖➖➖➖➖➖ ⠀ ╚════ ღ 𝔻ℕℤ 𝕋𝔼𝕄𝔸𝕊 ღ ══╝

📱 𝐃𝐍𝐙 𝐓𝐄𝐌𝐀𝐒 🔠🔠 >> 🔠🔠🔠 📢 𝗖𝗵𝗮𝗻𝗻𝗲𝗹: @DNZ_Temas #Mickey#Minnie ➖➖➖➖➖➖➖➖➖➖➖➖ 🔗𝗔𝗣𝗣𝗟𝗬 𝗧𝗛𝗘𝗠𝗘>> 𝕋𝔼𝕃𝔼𝔾ℝ𝔸𝕄 ✅ ⤵️𝗕𝗔𝗖𝗞𝗚𝗥𝗢𝗨𝗡𝗗>> ⬇️𝗪𝗔𝗟𝗟𝗣𝗔𝗣𝗘𝗥>> ➖➖➖➖➖➖➖➖➖➖➖➖ ╚════ ღ 𝔻ℕℤ 𝕋𝔼𝕄𝔸𝕊 ღ ══╝

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