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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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TonOrbital

@tonorbital · Post #831 · 09/20/2024, 09:18 PM

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💫 Today’s Highlights in the Ton Ecosystem, September 20 💫 📰The Daily TON: $CATI token listing causes Open League pause for two weeks to handle stress on TON Blockchain. 🔥Bitget Wallet: The new #BitgetWallet#Task2Get season offers a 300,000 $BEVM prize pool with double rewards up to $200 for new users—no NFT needed! 🌐 TON Community: TON Memelandia is evolving into a decentralized land of memes with upcoming battles, prizes, and events—expect major announcements at MEMECON during Token2049! 🗿STON.fi: GemSquads Fifth Season is live—vote for your favorite farms, and $43,000 worth of $STON rewards will be distributed to top trading pairs based on votes! 🙏Catizen: $CATI farming is live with $86,000 in rewards—stake LP tokens in CATI/TON and CATI/USDT pools on STON.fi to earn a share of 20,000 STON until October 4! 🚀swap.coffee: $SP is now available in Swap.coffee's cashback system—earn tokens with every swap and claim them anytime!

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