Instructions to use Developer9215/audio_cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Developer9215/audio_cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Developer9215/audio_cls")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Developer9215/audio_cls") model = AutoModelForAudioClassification.from_pretrained("Developer9215/audio_cls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Developer9215/audio_cls: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/Developer9215/audio_cls/resolve/main/training_args.bin
- Command line
-
hf download hf://Developer9215/audio_cls/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Developer9215/audio_cls/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 71b4f4aa46f54cb100529ecfc7a6ea74e6529914bea816809606f7fb6988dab0
- Size of remote file:
- 5.78 kB
- SHA256:
- ff625b2945a82661d5486d60359f9da4109c9fd40f097a97ec049d3471e60e91
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