Audio Classification
Transformers
PyTorch
TensorBoard
hubert
Generated from Trainer
Eval Results (legacy)
Instructions to use sandychoii/audio-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sandychoii/audio-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="sandychoii/audio-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("sandychoii/audio-classification") model = AutoModelForAudioClassification.from_pretrained("sandychoii/audio-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sandychoii/audio-classification: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/sandychoii/audio-classification/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://sandychoii/audio-classification@refs/pr/1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sandychoii/audio-classification/resolve/refs%2Fpr%2F1/training_args.bin
3.96 kB
- Xet hash:
- 3d8803edc28710b3248eb409e75365600b09ca52a7b0ce9eeab9cb516b3593cd
- Size of remote file:
- 3.96 kB
- SHA256:
- dec15cb7815a1de79ef137b6b157769c1b42dc42b92fa47a41d32ebfdfd5e7bf
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