Instructions to use Alfiyani/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alfiyani/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Alfiyani/audio_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Alfiyani/audio_classification") model = AutoModelForAudioClassification.from_pretrained("Alfiyani/audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Alfiyani/audio_classification: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Alfiyani/audio_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Alfiyani/audio_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Alfiyani/audio_classification/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 6a3db0fa9206811620d9f87d48cb575a2fe8065837f3319b44310b9bb5fecee0
- Size of remote file:
- 378 MB
- SHA256:
- 59f4c0378e0ef441cc016e7b822da01da435ab0b9e70de187a2f740cbb83a900
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