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Source channel @githubtrending · Post #14909 · Jul 3

#other#agent#llm#rag Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research. https://github.com/datawhalechina/happy-llm

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djangoproject

@djangoproject · Post #261 · 02/16/2017, 06:56 AM

http://www.giantflyingsaucer.com/blog/?p=5557 In spring 2014 Python 3.4 shipped a provisional package (#asyncio) which according to the docs “provides infrastructure for writing single-threaded #concurrent code using #coroutines, #multiplexing I/O access over #sockets and other resources, running network clients and servers, and other related primitives“. I can’t possibly cover everything in this article but I can introduce some of the things you can do with it. As per my New’s Years resolution I’ll be building these #examples using Python 3.4.2 (Asyncio has been ported back to Python 3.3 now as well).