Automatic Speech Recognition
Transformers
Safetensors
Yue Chinese
whisper
cantonese
romanization
jyutping
asr
liujgoj
Instructions to use Yvthyvq/Liujgoj-Cantonese-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yvthyvq/Liujgoj-Cantonese-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Yvthyvq/Liujgoj-Cantonese-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Yvthyvq/Liujgoj-Cantonese-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("Yvthyvq/Liujgoj-Cantonese-whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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| 總轉寫樣本數 | 4,742 條 | 4,742 條 |
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| 平均文本長度 | 98.93 字元 | 102.50 字元 |
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| 完全一致率 | 0.00% (0 條) | 0.00% (0 條) |
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| 平均文本相似度 | 71.25% | 71.25% |
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| 混入漢字樣本數 | 827 條 (17.44%) | 10 條 (0.21%) |
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| 漢字總字數 | 16,941 字 | 57 字 |
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| 總轉寫樣本數 | 4,742 條 | 4,742 條 |
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| 平均文本長度 | 98.93 字元 | 102.50 字元 |
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| 平均文本相似度 | 71.25% | 71.25% |
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| 混入漢字樣本數 | 827 條 (17.44%) | 10 條 (0.21%) |
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| 漢字總字數 | 16,941 字 | 57 字 |
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