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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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郭子健Daniel Kwok Tsz Kin

@tsingyidan · Post #1175 · 04/11/2025, 06:52 AM

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We successfully hosted the Citizenship and Settlement Seminar in Glasgow and Edinburgh this April — supporting Hongkongers on their journey to ILR and UK citizenship. This seminar was co-organised by The Hong Kong Scots CIC, Hong Kong Professionals CIC, ACRHK, and Glasgow Hong Kong Christian Church, with funding from COSLA (Convention of Scottish Local Authorities) under the BN(O) Integration Support Service. Special thanks to Henry Wong, solicitor qualified in both Hong Kong and England & Wales, for leading two in-depth legal workshops tailored for the community. We are deeply grateful to Corstorphine Community Church for their long-standing support and for kindly hosting our Edinburgh session. Full income & expenditure report (in English):https://www.patreon.com/posts/citizenship-and-126410655 #BNO#ILR#HongKongInScotland#CommunitySupport

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