Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-base-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-base-semantic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-base-semantic")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-base-semantic") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-base-semantic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "test_clean_stortinget_no": { | |
| "cer": 8.135327811431162, | |
| "exact_cer": 8.84279122480369, | |
| "exact_wer": 17.852185559478876, | |
| "wer": 13.78472306608015 | |
| }, | |
| "test_nst": { | |
| "cer": 1.7085944075563453, | |
| "exact_cer": 1.8461877600507013, | |
| "exact_wer": 6.47647155271356, | |
| "wer": 5.574684374487621 | |
| } | |
| } |