Instructions to use Jurabek/AudioClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jurabek/AudioClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Jurabek/AudioClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Jurabek/AudioClassification") model = AutoModelForAudioClassification.from_pretrained("Jurabek/AudioClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jurabek/AudioClassification: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Jurabek/AudioClassification/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://Jurabek/AudioClassification@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jurabek/AudioClassification/resolve/refs%2Fpr%2F1/training_args.bin
4.54 kB
- Xet hash:
- fb83d6dbf95d9eaa2ce42ee1f1984ce7e9d2edd7075993cdef8ccdd90ee7127c
- Size of remote file:
- 4.54 kB
- SHA256:
- e5cc735e157f9801e030937ea4a1fc9896f4838e6cd8bd59ed4637b7d9d70045
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