#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
💡 今日金句
当你停止创造,你的才能就不再重要,你所拥有的只剩下你的品味。
而品味会裹挟你,让你排斥他人、变得狭隘。
所以,创造。
When you don’t create things, you become defined by your tastes rather than
ability. your tastes only narrow & exclude people. so create.― Why The Lucky
Stiff
via 今日金句
标签: #create#your#tastes
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