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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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Luna Everly

@lunaeverly · Post #23 · 01/19/2026, 02:07 PM

Hey, I'm Luna. 🌙✨ A psychology student who believes the most important conversations sometimes happen not in an office, but over a cup of tea, in a cozy sweater, with the sound of rain against the window. Here I'll share my thoughts, snippets of my life, and a quiet belief that understanding can be found in this world. And photos — I love capturing things that are beautiful, simple, and genuine. Glad you're here. #lunaeverly#thinkingoutloud#support#everydaypsychology#cozy#personaldiary Привет, я Луна. 🌙✨ Студентка-психолог, которая верит, что самые важные разговоры иногда случаются не в кабинете, а за чашкой чая, в уютном свитере и под звук дождя за окном. Здесь я буду делиться своими мыслями, моментами из жизни и тихой уверенностью, что в этом мире можно найти понимание. А ещё фотографиями — мне нравится ловить красивое, простое и настоящее. #лунаэверли#мысливслух#поддержка#психологияповседневности#уют#личныйдневник