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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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@tuttoelezioni · Post #1356 · 10/27/2025, 07:15 AM

#Argentina🇦🇷 #Parlamentari Risultati parziali. Camera dei deputati. Sezioni scrutinate: 108.125/108.992 (99,20%). 🟪 La Libertà Avanza (#LLA|Libertaristi di destra): 40,65% (64) 🟦 Forza Patria (#FP|Centrosinistra peronista): 24,31% (31) 🟦 Province Unite (#PU|Centro): 4,96% (5) 🟥 Fronte di Sinistra (#FITU|Trotskisti): 3,71% (3) 🟦 Fronte Prima il Tucumán (#FTP): 2,28% (2) 🟥 Fronte Civico per Santiago (#FCS): 1,23% (2) 🟦 Forza Giustizialista Mendoza (#FJM): 1,10% (1) 🟦 Forza Entre Ríos (#FER): 1,06% (2) 🟪 Proposta federale per il cambiamento (#PFC): 1,05% (0) Altri: 19,65% (17) N.B.: Tra parentesi sono indicati i seggi ottenuti. @TuttoElezioni