Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Norwegian
whisper
whisper-event
norwegian
Eval Results (legacy)
Instructions to use NbAiLab/whisper-small-nob with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/whisper-small-nob with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/whisper-small-nob")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/whisper-small-nob") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/whisper-small-nob", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NbAiLab/whisper-small-nob: direct link, hf CLI and curl.
- Browser
- Download file 484 MB
-
https://huggingface.co/NbAiLab/whisper-small-nob/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NbAiLab/whisper-small-nob/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NbAiLab/whisper-small-nob/resolve/main/pytorch_model.bin
484 MB
- Xet hash:
- 84a90efb8f9a4ca5a3d0ec05d7375bf86c05adf6828c1f6dafa1d45f2340346b
- Size of remote file:
- 484 MB
- SHA256:
- 0c58db416b6a398acffa0cad768bfe2798fea100412fc3f0423b920ddabd5f0b
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