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Source channel @githubtrending · Post #15385 · Jan 2

#python#deep_learning#inference#openai#quantization#speech_recognition#speech_to_text#transformer#whisper Faster-Whisper is a fast version of OpenAI's Whisper that transcribes audio up to 4x quicker with the same accuracy, using less memory on CPU or GPU—benchmarks show it beats original Whisper (e.g., 1m03s vs 2m23s for 13-min audio on GPU). Install via `pip install faster-whisper`, no FFmpeg needed, and use simple Python code like `WhisperModel("large-v3").transcribe("audio.mp3")` for segments with timestamps. You benefit by getting quick, efficient speech-to-text for real-time apps, saving time and resources on long files or batches. https://github.com/SYSTRAN/faster-whisper

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djangoproject

@djangoproject · Post #435 · 09/07/2017, 01:47 PM

https://www.python.org/dev/peps/pep-0498/ #Interpolation # Python supports multiple ways to format text strings. # These include %-formatting, # str.format(), # and string.Template # The !s, !r, and !a conversions are not strictly required. # Because arbitrary expressions are allowed inside the #f_strings, # this code: »> a = 'some string' »> f'{a!r}' "'some string'" Is identical to: »> f'{repr(a)}' "'some string'" Similarly, !s can be replaced by calls to #str() and !a by calls to #ascii().

djangoproject

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

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