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:
- 2f2b887ad39f46af5887092ba1e7dc5f694f65cc0d63a2adcf2de2cc3d51ad55
- Size of remote file:
- 3.06 kB
- SHA256:
- cba0407afeb94e5c61fb60760555d3e67958b71b4ae430dc28c3be8ab33d4a2d
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