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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 M - Crypto News

@CryptoM · Post #65388 · 04/13/2026, 04:14 AM

🚀 AINFT Platform Surpasses 700,000 Users, Advances in Web3 AI The AINFT platform has officially exceeded 700,000 users, according to official data. According to Odaily, the growing user base and the continuous enhancement of AI model capabilities are propelling it to become a leading AI platform in the Web3 sector. AINFT currently offers users AI models ready for production and fully supports the execution of on-chain automated workflows, facilitating a rapid transition from creative ideas to on-chain implementation. Leveraging its expanding community and open technical architecture, AINFT aims to lower the barriers to using Web3 AI, enabling more efficient deployment of innovative applications. #AINFT#700000Users#Web3#AIPlatform#AI#Blockchain#OnChain#AutomatedWorkflows#Web3AI#Innovation#Technology#Community