Instructions to use LenixC/distilhubert-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LenixC/distilhubert-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="LenixC/distilhubert-finetuned-gtzan")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("LenixC/distilhubert-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("LenixC/distilhubert-finetuned-gtzan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from LenixC/distilhubert-finetuned-gtzan: direct link, hf CLI and curl.
- Browser
- Download file 94.8 MB
-
https://huggingface.co/LenixC/distilhubert-finetuned-gtzan/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://LenixC/distilhubert-finetuned-gtzan/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/LenixC/distilhubert-finetuned-gtzan/resolve/main/pytorch_model.bin
94.8 MB
- Xet hash:
- aa37ebb192e00b434cef8bbeda077b7fd00a1f16581ed4a3bd26774399e6e5bb
- Size of remote file:
- 94.8 MB
- SHA256:
- 5c08d9132b98a1e039cf494e5b7466760b9bc82502cb03ab86169d33ce81fe76
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