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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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@singsingchannel · Post #1127 · 12/23/2024, 07:11 AM
🔥 Another 121,343 $SING has been burned! 🔥 💨 Reducing supply, increasing value—step by step, we're building a stronger $SING ecosystem. ✔️Check out details: https://bscscan.com/tx/0xb3fac74c5744b68eee62ffa0efbdbe909ec4e719c2b644315a082c32a3aa9634 Stay tuned for more updates! 🚀 #SingSing#TokenBurn#Deflation
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@venturevillagewall · Post #4114 · 02/10/2025, 01:00 PM
Ethereum: Potential Shift to Trustworthy Money Ethereum could become ‘ultra-secure’ money as supply decreases, claims developer Justin Drake. Post-Dencun, emissions stats: 657,000 BTC vs. 469,000 ETH ($63.4B vs. $1.23B). Bitcoin miners rely on crypto mining; commission share at only 1%. Safety concerns may arise as mining becomes less viable. Halvings could worsen security issues. Read more: ForkLog #Ethereum#Bitcoin#Crypto#Mining#Finance#Deflation#JustinDrake#Dencun#ETH#BTC#Blockchain#Investing#Decentralization#PoS#Halving#Security#MarketTrends#Emissions#DigitalAssets#RiskManagement#Cryptocurrency