|
--- |
|
license: mit |
|
datasets: |
|
- mozilla-foundation/common_voice_11_0 |
|
language: |
|
- ja |
|
pipeline_tag: automatic-speech-recognition |
|
tags: |
|
- pytorch |
|
- faster-whisper |
|
- whisper |
|
- CTranslate2 |
|
metrics: |
|
- wer |
|
--- |
|
|
|
Converted from [clu-ling/whisper-large-v2-japanese-5k-steps](https://huggingface.co/clu-ling/whisper-large-v2-japanese-5k-steps) using [CTranslate2](https://github.com/OpenNMT/CTranslate2). |
|
|
|
Usage: |
|
1. Install `pip install faster-whisper` (Check [faster-whisper](https://github.com/guillaumekln/faster-whisper) for detailed instructions.) |
|
|
|
2. ```python |
|
from faster_whisper import WhisperModel |
|
|
|
model = WhisperModel('zh-plus/faster-whisper-large-v2-japanese-5k-steps', device="cuda", compute_type="float16") |
|
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)) |
|
``` |
