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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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Crypto News & Web3 Events | TON Ecosystem

@tonevents_en · Post #1201 · 01/26/2025, 06:11 PM

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🎁 Split Introduces Gift Code Feature for Seamless Rewards #Split now allows users to create unique gift codes on the #TON network with just a few clicks. This feature enables you to generate personalized gifts for friends or loved ones. Recipients can easily activate the code and instantly enjoy their rewards, all while benefiting from the fast and hassle-free payments of the TON blockchain. 🌀Connect your wallet and start gifting today!

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🇨🇺 Anuncios-cu | Publicitaria

@anuncios_cu · Post #4847 · 01/17/2025, 09:56 PM

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