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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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@PensivePost · Post #5350 · 08/07/2021, 11:32 PM

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The beau, ignorance. I knew. That made me a shitty person If there was anything that made it unbearable and more hard to overcome than anything, it’s the fact that I knew it was going to happen. It’s a pity we don’t get to un-know stuff. Like just trash it. It felt(no, was )wrong. Like hoarding the girls lavatory or cyber bullying overweight people because it felt right Or self-hurting so you can feel anything other than this unimaginable sorrow that was slowly drowning you. If there was anything that was worse than knowledge, it’ll be passivity, more like apathy. The fact that you didn’t act. That I didn’t act This didn’t feel wrong. It didn’t feel like anything I have ever felt. Words can’t quantify how it feels. Probably, nothing will. I hope nothing does. Excerpt from my book, For the Lies that Matter @whosayegat #review #everyone #excerpts

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