Instructions to use nacielo/whispherMusic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nacielo/whispherMusic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nacielo/whispherMusic")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nacielo/whispherMusic") model = AutoModelForSpeechSeq2Seq.from_pretrained("nacielo/whispherMusic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a44b809398c5171c0b4453fd7de43ef68cd1dedcd060ceede1e4d2b43c85b3c5
- Size of remote file:
- 290 MB
- SHA256:
- 17f115713724565bb926de8726205cb19bc9fbae078eabd53305aa3f3eec216f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.