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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
How to unlock 120 fps smooth browsing in Safari
Find out how to force Safari on iPhone, iPad, and Mac to render webpages at
120Hz instead of 60Hz on devices with a ProMotion display.
via iDB - Mac
标签: #Safari#Hz#How
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