Audio Classification
Transformers
PyTorch
TensorBoard
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use Apocalypse-19/distilhubert-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apocalypse-19/distilhubert-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Apocalypse-19/distilhubert-finetuned-gtzan")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Apocalypse-19/distilhubert-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("Apocalypse-19/distilhubert-finetuned-gtzan") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 893e5dfaa3013ff92d32e901455bb5ca3fc4366d46eec8f66587b8c89b9ffe76
- Size of remote file:
- 94.8 MB
- SHA256:
- 439a6c5f8c01f053fbee91b7c3cb824dbf9ead8b1f92fee7d516c70623787bf4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.