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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 118a7d6f8f92ab504de4ddffc0f4094c44900ffc3c4608a19199cf21378a7630
- Size of remote file:
- 378 MB
- SHA256:
- 97ac29367e722162a47630284b156d909715d71464ec40b05374fbbce335ba39
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