Instructions to use JunWorks/Quantized_4bit_WhisperSmallStd_zhTW with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JunWorks/Quantized_4bit_WhisperSmallStd_zhTW with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="JunWorks/Quantized_4bit_WhisperSmallStd_zhTW")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("JunWorks/Quantized_4bit_WhisperSmallStd_zhTW") model = AutoModelForSpeechSeq2Seq.from_pretrained("JunWorks/Quantized_4bit_WhisperSmallStd_zhTW") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model Details
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On test set for CommonVoice13.0 zh-TW <br>
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CER: 11.3958% <br>
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(for reference: 8-bit CER: 10.2803%, non quantized CER: 10.3295%)
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## Model Details
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