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license: cc-by-4.0
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---
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---
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license: cc-by-4.0
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language:
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- is
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datasets:
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- language-and-voice-lab/samromur_asr
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- language-and-voice-lab/samromur_children
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- language-and-voice-lab/malromur_asr
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- language-and-voice-lab/althingi_asr
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tags:
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- audio
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- automatic-speech-recognition
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- icelandic
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- whisper
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- whisper-large
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- iceland
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- reykjavik
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- samromur
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- faster-whisper
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---
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# whisper-large-icelandic-30k-steps-1000h-ct2
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This is a faster-whisper version of [language-and-voice-lab/whisper-large-icelandic-30k-steps-1000h](https://huggingface.co/language-and-voice-lab/whisper-large-icelandic-30k-steps-1000h).
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The model was created as such like described in [faster-whisper](https://github.com/guillaumekln/faster-whisper/tree/master):
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```bash
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ct2-transformers-converter --model language-and-voice-lab/whisper-large-icelandic-30k-steps-1000h \
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--output_dir whisper-large-icelandic-30k-steps-1000h-ct2 \
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--quantization float16
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```
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# Usage
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```python
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from faster_whisper import WhisperModel
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model_size = "whisper-large-icelandic-30k-steps-1000h-ct2"
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# Run on GPU with FP16
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model = WhisperModel(model_size, device="cuda", compute_type="float16")
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# or run on GPU with INT8
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# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
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# or run on CPU with INT8
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# model = WhisperModel(model_size, device="cpu", compute_type="int8")
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segments, info = model.transcribe("audio.mp3", beam_size=5)
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print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
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for segment in segments:
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print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
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```
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