Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Saving test results
Browse files
runs/Jan07_21-39-59_t1v-n-3c897cb1-w-4/events.out.tfevents.1704663599.t1v-n-3c897cb1-w-4.18033.0.v2
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test_results.json
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{
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"test_clean_stortinget_no": {
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"cer": 6.631227593027568,
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"exact_cer": 7.258965433497935,
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"exact_wer": 14.606112261049557,
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"wer": 10.827034777748073
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},
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"test_nst": {
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"cer": 0.9482839240624708,
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"exact_cer": 1.0672985956114005,
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"exact_wer": 3.825763786413073,
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"wer": 3.0496802754549925
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}
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}
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