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Source channel @githubtrending · Post #14798 · Jun 6

#jupyter_notebook Unsloth is a tool that makes it much faster and easier to fine-tune large language models like Llama, Mistral, and Gemma, even on regular computers or single GPUs. It uses smart tricks to speed up training by 2 to 5 times and cuts memory use by up to 70%, so you can train models quickly without needing expensive hardware[1][3][4]. The benefit is that anyone—developers, researchers, or AI fans—can create custom AI models for different tasks, from chatting to vision, in less time and with less hassle, using ready-made notebooks and guides for popular models[3][5]. https://github.com/unslothai/notebooks

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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).