Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-medium")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-medium") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
d3a8e74 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:791bf90eeab5ff2b92573c147e0140b325330eff1509084f9e041fbdf5e56307
size 3055465603
|