Instructions to use phi0108/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phi0108/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="phi0108/audio_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("phi0108/audio_classification") model = AutoModelForAudioClassification.from_pretrained("phi0108/audio_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6ef073e527ba222bd7ac2300d42aa30fe90f42dd7c10d3e1ae1fa92880efb03
- Size of remote file:
- 3.58 kB
- SHA256:
- 38cbb409b8d70459c2be15f8c59299c9cbab306d0bd2817994c6581d1daf3b9c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.