Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74a05662ab9c057ed8a94dbcda03dd989ad56d99b830366a922ac98931b71f34
- Size of remote file:
- 77.7 MB
- SHA256:
- 2f9dd799ee36b6a9c8d642e9b1df8ecf2135efdd5a91b1d9ca0b3c0decda535f
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