Instructions to use codingaslu/Hubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codingaslu/Hubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="codingaslu/Hubert")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("codingaslu/Hubert") model = AutoModelForAudioClassification.from_pretrained("codingaslu/Hubert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c55f9717e26e4504a0322d147e36479b15b4c133d21b8504f4d87178c86f464
- Size of remote file:
- 1.26 GB
- SHA256:
- b1a996c51fc46986f9de049efe3c442e85f28b91bfd07e06cba7f3ffbf0d5f74
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