Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-medium-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-medium-beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-medium-beta")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-medium-beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-medium-beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 60468e29fb2380fae32a1565a9d2e89865321ccc8f2d1da3b2ddecfff3fbbb32
- Size of remote file:
- 22.3 kB
- SHA256:
- e05de2dcb46e6f598bb875c7fa2d10a7439794fcda758c55e876e76962a552e5
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