Instructions to use dima806/classical_composer_classification-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/classical_composer_classification-new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/classical_composer_classification-new")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dima806/classical_composer_classification-new") model = AutoModelForAudioClassification.from_pretrained("dima806/classical_composer_classification-new", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b81dcaf163eabd2c899a91c84670757f9fb61a61f2fb5db57fcaf615c6f2d55e
- Size of remote file:
- 3.57 kB
- SHA256:
- 79a6312bbebb062a7cc6c7757e6db35ceed7ff755dff95ea9882c68ce3d8f694
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.