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Source channel @githubtrending · Post #15586 · Mar 26
#jupyter_notebook Insanely Fast Whisper is a simple CLI tool that transcribes audio files super quickly on your NVIDIA GPU or Mac using OpenAI's Whisper Large v3 model with optimizations like Flash Attention 2. Install via `pipx install insanely-fast-whisper` and run `insanely-fast-whisper --file-name youraudio.mp3 --flash True` to transcribe 150 minutes of audio in under 98 seconds. You benefit by saving hours on tasks like podcasting or meetings, getting accurate text output fast without cloud costs or slow processing. https://github.com/Vaibhavs10/insanely-fast-whisper
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@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.
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@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.