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NbAiLab
/
whisper-large-sme

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Northern Sami
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
2

Instructions to use NbAiLab/whisper-large-sme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use NbAiLab/whisper-large-sme with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="NbAiLab/whisper-large-sme")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("NbAiLab/whisper-large-sme")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/whisper-large-sme", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
whisper-large-sme / runs /Dec15_08-48-40_dante
17.1 kB
Ctrl+K
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  • 3 contributors
History: 2 commits
versae's picture
versae
Model save
90cdc62 over 3 years ago
  • 1671090620.3211656
    Training in progress, step 60000 over 3 years ago
  • events.out.tfevents.1671090620.dante.1681436.0
    11.3 kB
    xet
    Model save over 3 years ago