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Source channel @githubtrending · Post #14826 · Jun 12

#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data. https://github.com/FareedKhan-dev/all-rag-techniques

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DWF Labs Broadcast

@Dwflabs · Post #139 · 01/12/2023, 01:16 AM

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[5 Jan to 11 Jan] DWF Crypto Snapshot 🗞️ Our latest #crypto report by DWF Labs Managing Partner Andrei Grachev is up here. Here's your weekly round up 🚀 💠Decentralized Exchange Aggregators See Uptick In Utility 💠Stablecoins Are The New #CBDCs In Hong Kong's Latest Proposal 💠World Mobile Token Launches #EarthNode NFTs On Cardano 💠It's All About The #Experience For The Future Of #NFTs 💠Innovation, #Integration, and Community is Key To A Successful #Blockchain, Says Comparing Layer-1 Platforms: 2022 Edition by The Block 💠Skip The Wait On #NFT Trading With NFT Decentralized Exchanges 💠More Web3 Projects Join Initiatives To Create Safer Blockchain #Ecosystems 💠Ethereum Staking #Protocols Will See A Boom Post-Shanghai Missed last week's snapshot? Read here. Follow us on Medium here. Stay up-to-date on the latest DWF Labs updates: Website| Twitter | Linkedin | Telegram

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