Instructions to use Ammok/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammok/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Ammok/audio_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Ammok/audio_classification") model = AutoModelForAudioClassification.from_pretrained("Ammok/audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ammok/audio_classification: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Ammok/audio_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://Ammok/audio_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ammok/audio_classification/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 4b8effbeb123d07c8f1384fc6f52cb06e8ba5855c42bbd6c84aca9a977316aea
- Size of remote file:
- 3.96 kB
- SHA256:
- 61051710214016c3606dda7e268db40130084ca4d838c707853aa8ac0b1cfcc1
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