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
Ctrl+K
- ct2
- onnx
- predictions
- runs
- 1.61 kB
- 20.3 kB
- 34.6 kB
- 3.65 kB
- 4.49 kB
- 2.14 kB
- 151 MB xet
- 3.82 kB
- 3.79 kB
- 29.9 MB xet
- 77.7 MB xet
- 494 kB
- 151 MB xet
- 151 MB xet
- 261 Bytes
- 52.7 kB
- 339 Bytes
- 151 MB xet
- 312 Bytes
- 2.19 kB
- 6.38 kB
- 364 Bytes
- 151 MB xet
- 3.93 MB
- 283 kB
- 6.3 kB xet
- 494 kB
- 836 kB
- 822 Bytes
- 1.04 MB
- 1.07 MB