Audio Classification
Transformers
PyTorch
TensorBoard
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use ashish-soni08/distilhubert-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashish-soni08/distilhubert-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="ashish-soni08/distilhubert-finetuned-gtzan")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("ashish-soni08/distilhubert-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("ashish-soni08/distilhubert-finetuned-gtzan") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b16186bb517091a6fce99a3af1395b61ad27b258ca3793ce177e6f9bcf298fb9
- Size of remote file:
- 4.03 kB
- SHA256:
- 8ff2b33536ea569a4f69b4216ca2897b47cd10f156fa46fdd74efcbd1e3efd8d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.