Instructions to use Jurabek/Audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jurabek/Audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Jurabek/Audio_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Jurabek/Audio_classification") model = AutoModelForAudioClassification.from_pretrained("Jurabek/Audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jurabek/Audio_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/Jurabek/Audio_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Jurabek/Audio_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jurabek/Audio_classification/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 708863bb7367afe6cc9d336384d70fc1a81ea0db7b55d770bcf7a0630689721b
- Size of remote file:
- 4.54 kB
- SHA256:
- a4fa9d18687a3489ff2f1f48c69e6f344eea2384c22881c2805f4972d3c6bc77
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