Instructions to use dima806/multiple_accent_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/multiple_accent_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dima806/multiple_accent_classification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dima806/multiple_accent_classification") model = AutoModelForAudioClassification.from_pretrained("dima806/multiple_accent_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1057b0c0c42a0d55eceff801e213830638925f71c71208f63cf382554742b0eb
- Size of remote file:
- 3.57 kB
- SHA256:
- 5e586ffec83af94e0cf9ea31750e6c3ca1bf1ee016bdd398b7fe339f74b71c58
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