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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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@dzdigital3 · Post #18717 · 07/23/2025, 12:08 PM

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☀️Beck’s☀️

@beck_blog · Post #819 · 12/21/2020, 05:31 PM

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· · • • • •❄️• · · INSTAGRAM· · •❄️• • • • · · ⇝•❄️• El gato es el animal más popular en Instagram ya que a día de hoy existen casi 450 millones de publicaciones con hashtags como #cat, #gato, #catlover o #catlife. Muy por detrás le sigue el perro, con una media de 340 millones de publicaciones con etiquetas como #dog, #doglover o #perrosfelices. · · • • • • • · · · · • • • ☃️• • • · · · · • • • • • · ·

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