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openai/whisper-large-v3-turbo üzerine LoRA fine-tune. Çok-domain dengeli all-rounder (clean + robustluk + medikal birlikte korunur).
CTranslate2 (float16) derlemesi — faster-whisper / WhisperX ile hızlı çıkarım.1from faster_whisper import WhisperModel
2model = WhisperModel("RsGoksel/RsGoksel_ITU_Mainframe-balanced-ct2", device="cuda", compute_type="float16")
3segments, _ = model.transcribe("audio.wav", language="tr",
4 condition_on_previous_text=False, beam_size=5)
5text = " ".join(s.text for s in segments).strip()1import whisperx
2m = whisperx.load_model("RsGoksel/RsGoksel_ITU_Mainframe-balanced-ct2", device="cuda", compute_type="float16",
3 language="tr", asr_options={"condition_on_previous_text": False})
4res = m.transcribe("audio.wav", language="tr")
5text = " ".join(s["text"] for s in res["segments"])language="tr", condition_on_previous_text=False.
Metrik: Türkçe normalizasyon sonrası mean-per-utterance WER.RsGoksel/RsGoksel_ITU_Mainframe-balanced.