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Source channel @githubtrending · Post #15618 · Apr 15

#jupyter_notebook This free tutorial series teaches hands-on large model skills like fine-tuning, prompting, math reasoning, jailbreaks, agents, and safety alignment, with slides, guides, code notebooks, and new Huawei Ascend courses (PPTs, videos) for full development workflows. You'll quickly master AI models through simple practices, boosting your course projects, research, or career in large language models. https://github.com/Lordog/dive-into-llms

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djangoproject

@djangoproject · Post #98 · 07/11/2016, 12:22 PM

https://docs.python.org/3/library/asyncio.html #asyncio #Asynchronous programming is more complex than classical “#sequential” programming: see the Develop with asyncio page which lists common traps and explains how to avoid them. Enable the debug mode during development to detect common issues.

djangoproject

@djangoproject · Post #153 · 09/03/2016, 08:20 PM

http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.