Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Norwegian
Norwegian Bokmål
wav2vec2
Eval Results (legacy)
Instructions to use NbAiLab/nb-wav2vec2-300m-bokmaal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-wav2vec2-300m-bokmaal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-wav2vec2-300m-bokmaal")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("NbAiLab/nb-wav2vec2-300m-bokmaal") model = AutoModelForCTC.from_pretrained("NbAiLab/nb-wav2vec2-300m-bokmaal") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4dbc2876a3146bdb44ce6997152d0c5762c5fdaa95396e98e0e74cab6789fe6b
- Size of remote file:
- 1.26 GB
- SHA256:
- 146aae60aca5aad96c2d676908ba62300d18e34ec2cc31c921f29458eacbf2a7
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