Audio Classification
Transformers
PyTorch
TensorBoard
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use adbcode/distilhubert-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adbcode/distilhubert-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="adbcode/distilhubert-finetuned-gtzan")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("adbcode/distilhubert-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("adbcode/distilhubert-finetuned-gtzan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from adbcode/distilhubert-finetuned-gtzan: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/adbcode/distilhubert-finetuned-gtzan/resolve/main/training_args.bin
- Command line
-
hf download hf://adbcode/distilhubert-finetuned-gtzan/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/adbcode/distilhubert-finetuned-gtzan/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 3d4aee906e591a06b5d3459f62f04ca73a2862c6e4ace3bc1edb8e29903dbc2c
- Size of remote file:
- 4.03 kB
- SHA256:
- 7f1b961582ba7fca0a3a137166592ef76034d7b500e1758f8560ab805590493d
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