Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-large-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-large-beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-large-beta")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-large-beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-large-beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc4dda913221d691e16efdfc0a18987e934eab6a1bc35bed335f61d6ead98885
- Size of remote file:
- 21.2 kB
- SHA256:
- 7f1d95fcdb53e701568e0e7368ca7a71f6681448aad5eb6c50092a721e44f6d1
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