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Source channel @githubtrending · Post #14993 · Jul 24

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#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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Quiet World 🍁

@QuietWorld · Post #7450 · 06/27/2020, 11:02 PM

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Shopping for Henoa le Kitten again! 😍 Unplanned but I found item that I didn't know exist before that I think Henoa & I needs and I read lots of reviews saying that this shop sells a lot cheaper than other stores so why not? 😂 Will be making a video of unboxing these + review once they arrived and tested 🥰💞 Stay tuned for this video upload in my channel 🥰 #marcegetaway#youtube#kitten#Henoa @quietworld🍃

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