---
license: cc-by-4.0
language:
- is
datasets:
- language-and-voice-lab/samromur_asr
- language-and-voice-lab/samromur_children
- language-and-voice-lab/malromur_asr
- language-and-voice-lab/althingi_asr
tags:
- audio
- automatic-speech-recognition
- icelandic
- whisper
- whisper-large
- iceland
- reykjavik
- samromur
- faster-whisper
---
# whisper-large-icelandic-30k-steps-1000h-ct2

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).

The model was created like described in [faster-whisper](https://github.com/guillaumekln/faster-whisper/tree/master):

```bash
ct2-transformers-converter --model language-and-voice-lab/whisper-large-icelandic-30k-steps-1000h \
    --output_dir whisper-large-icelandic-30k-steps-1000h-ct2 \
    --quantization float16
```

# Usage

```python
from faster_whisper import WhisperModel

model_size = "whisper-large-icelandic-30k-steps-1000h-ct2"

# Run on GPU with FP16
model = WhisperModel(model_size, device="cuda", compute_type="float16")

# or run on GPU with INT8
# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
# or run on CPU with INT8
# model = WhisperModel(model_size, device="cpu", compute_type="int8")

segments, info = model.transcribe("audio.mp3", beam_size=5)

print("Detected language '%s' with probability %f" % (info.language, info.language_probability))

for segment in segments:
    print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
```