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 pytorch_model.bin from adbcode/distilhubert-finetuned-gtzan: direct link, hf CLI and curl.
- Browser
- Download file 94.8 MB
-
https://huggingface.co/adbcode/distilhubert-finetuned-gtzan/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://adbcode/distilhubert-finetuned-gtzan/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/adbcode/distilhubert-finetuned-gtzan/resolve/main/pytorch_model.bin
94.8 MB
- Xet hash:
- 1236c04f29a6b6d35c4726d05d33f6c4544a883cdd803d449c183839ce219ee0
- Size of remote file:
- 94.8 MB
- SHA256:
- 7fed37878bf93e8a975cf55b1acdad6caaf6157e2c47f8b35a2c27e2c9d42242
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