Instructions to use s15959/accent_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s15959/accent_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="s15959/accent_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("s15959/accent_classification") model = AutoModelForAudioClassification.from_pretrained("s15959/accent_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from s15959/accent_classification: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/s15959/accent_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://s15959/accent_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/s15959/accent_classification/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 35aadb6c060b5608ee93d69eb6c1b95f1cc3e1bc4a7e9ada6451643c09862fa5
- Size of remote file:
- 3.52 kB
- SHA256:
- 424dba3d037326873d80e4c7a8e285ccec1a89e0ca81a6407d09b2e365286d07
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