Instructions to use tomasolo/hubert_audio_classification_tomasolo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tomasolo/hubert_audio_classification_tomasolo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="tomasolo/hubert_audio_classification_tomasolo")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("tomasolo/hubert_audio_classification_tomasolo") model = AutoModelForAudioClassification.from_pretrained("tomasolo/hubert_audio_classification_tomasolo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tomasolo/hubert_audio_classification_tomasolo: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/tomasolo/hubert_audio_classification_tomasolo/resolve/main/training_args.bin
- Command line
-
hf download hf://tomasolo/hubert_audio_classification_tomasolo/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tomasolo/hubert_audio_classification_tomasolo/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- 71512d46153840a3139a2f7c16e32891b12c72306abd726b7016d3e2390c1e5f
- Size of remote file:
- 4.03 kB
- SHA256:
- 089a36e1525d828b866443cb1aeb4e64211ca674be9e6117a8c0c6c3116b1a34
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