Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-base")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-base") - Notebooks
- Google Colab
- Kaggle
Update test_results.json
Browse files- test_results.json +14 -0
test_results.json
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{
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"test_clean_stortinget_no": {
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"cer": 7.684509828161701,
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"exact_cer": 8.349388812434226,
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"exact_wer": 17.07536831851942,
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"wer": 13.199018154421951
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},
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"test_nst": {
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"cer": 1.5458711306462172,
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"exact_cer": 1.6836130170014605,
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"exact_wer": 5.815160955347872,
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"wer": 4.968027545499262
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}
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}
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