Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-medium-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-medium-semantic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-medium-semantic")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-medium-semantic") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-medium-semantic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0aed3e597cd9c4af660070cb195c0dd0baee207328adf08c8b0306f0bf57d76
- Size of remote file:
- 4.59 kB
- SHA256:
- aed1b19576bb226a589b99a409dc3a2078c29112c40cfed17dc5f6847b500f74
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