Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35fee8913101fd1cadd2820a16b6815b6d40858940ae36dfcd4f227abb1448b9
- Size of remote file:
- 6.34 kB
- SHA256:
- ef6f341ce686fb5a2c9064b5a0b9e2e5ad84961eff2b46f1773a6af52b6bf23c
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