Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-medium")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Saving test results
Browse files
runs/Jan07_21-34-09_t1v-n-ef12f06c-w-4/events.out.tfevents.1704663249.t1v-n-ef12f06c-w-4.15891.0.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": 5.804590596283018,
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"exact_cer": 6.340969804905691,
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"exact_wer": 12.71886034335809,
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"wer": 9.390721073225265
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},
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"test_nst": {
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"cer": 0.7294491723557468,
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"exact_cer": 0.8569617811578629,
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"exact_wer": 3.1972454500737824,
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"wer": 2.3938350549270373
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}
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}
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