Instructions to use michaelsh/distilhubert-finetuned-gtzan-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelsh/distilhubert-finetuned-gtzan-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="michaelsh/distilhubert-finetuned-gtzan-2")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("michaelsh/distilhubert-finetuned-gtzan-2") model = AutoModelForAudioClassification.from_pretrained("michaelsh/distilhubert-finetuned-gtzan-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from michaelsh/distilhubert-finetuned-gtzan-2: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/michaelsh/distilhubert-finetuned-gtzan-2/resolve/main/training_args.bin
- Command line
-
hf download hf://michaelsh/distilhubert-finetuned-gtzan-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/michaelsh/distilhubert-finetuned-gtzan-2/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 105d4b34147175e8948706f75e1dc196f489dea2083d5c0261fed877b9a8d482
- Size of remote file:
- 3.96 kB
- SHA256:
- 5a8354dc326f843935d0365262dd9a2d2c1c9ecddc6b717d50fa49ba59768733
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