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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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djangoproject

@djangoproject · Post #456 · 10/04/2017, 02:57 AM

http://www.techbeamers.com/python-tutorial-essentials-of-python-socket-programming/ Essentials of Python #Socket Programming You Should Know Python offers two types of #API libraries that we can use for socket programming. At the low-level, Python utilizes the “socket” library to implement #client and #server#modules for both #connectionless and #connection-oriented #network protocols. Whereas, at the higher-level, You can use libraries like #ftplib and #httplib to interact with application-level network protocols like #FTP and #HTTP.

djangoproject

@djangoproject · Post #513 · 11/30/2017, 10:00 PM

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