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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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Venture Village Wall 🦄

@venturevillagewall · Post #3507 · 12/19/2024, 03:57 PM

Monad Ecosystem's Rising Interest The Monad blockchain ecosystem is gaining attention ahead of its launch, focusing on community engagement and innovative projects. Key highlights include: - Event: Demo day showcased 20 projects, co-hosted by Paradigm with a $750k prize pool. - Projects: Noteworthy initiatives included: - Kizzy: A mobile betting platform based on Twitter events. - Sparkball: A team strategy game soon on Steam. - LootGO: A Walk2Earn project, previously overlooked. - Pulse: A health-monitoring bracelet securing $1.8M funding. - Community and Hype: Founders cite strong community support as a major attractor to Monad. - Future Vision: Excitement surrounds Monad’s upcoming testnet and potential partnerships with platforms like TON. #Blockchain#Monad#Crypto#Web3#Gaming#Social#Fundraising#EVMcompatible#Paradigm#DemoDay#Kizzy#Sparkball#LootGO#Pulse#NEOWIZ#Ethereum#Funding#TokenLaunch#Community#Hype