Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use NbAiLab/whisper-tiny-nob with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/whisper-tiny-nob with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/whisper-tiny-nob")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/whisper-tiny-nob") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/whisper-tiny-nob", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 349526fc10c210e037a1e120653914daae466787791b834a0bdc0b43cf8e327f
- Size of remote file:
- 151 MB
- SHA256:
- f2f29211d9a75bc3f14ea2f562dd9ffb53489d983276b9b49556da4bf31eae07
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