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NbAiLab
/
XLSR-300M-bokmaal

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use NbAiLab/XLSR-300M-bokmaal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NbAiLab/XLSR-300M-bokmaal with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="NbAiLab/XLSR-300M-bokmaal")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("NbAiLab/XLSR-300M-bokmaal")
    model = AutoModelForCTC.from_pretrained("NbAiLab/XLSR-300M-bokmaal")
  • Notebooks
  • Google Colab
  • Kaggle
XLSR-300M-bokmaal / language_model
4.26 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 1 commit
versae's picture
versae
Add lang model
fb09886 over 4 years ago
  • 5gram.bin
    4.24 GB
    xet
    Add lang model over 4 years ago
  • attrs.json
    78 Bytes
    Add lang model over 4 years ago
  • unigrams.txt
    16.8 MB
    xet
    Add lang model over 4 years ago