Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-large") - Notebooks
- Google Colab
- Kaggle
Recommended use is GPU, but code doesn't show examples of how to utilise GPU
#3
by MCMLXXXVII - opened
Do you have a method for using GPU when running? At the moment, it's CPU only, but the readme recommending otherwise
asr = pipeline("automatic-speech-recognition", "NbAiLabBeta/nb-whisper-large", device="cuda" )
MCMLXXXVII changed discussion status to closed