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NbAiLabBeta
/
nb-whisper-large

Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Model card Files Files and versions
xet
Metrics Training metrics Community

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

  • Libraries
  • Transformers

    How to use NbAiLabBeta/nb-whisper-large with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-large")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-large")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-large")
  • Notebooks
  • Google Colab
  • Kaggle
nb-whisper-large / ct2
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  • 1 contributor
History: 3 commits
pere's picture
pere
Update ct2/vocabulary.json
5a7d61b over 2 years ago
  • config.json
    2.39 kB
    Update ct2/config.json over 2 years ago
  • model.bin
    6.17 GB
    xet
    Update ct2/model.bin over 2 years ago
  • vocabulary.json
    1.07 MB
    Update ct2/vocabulary.json over 2 years ago