Instructions to use RamiEbeid/hubert-base-ser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RamiEbeid/hubert-base-ser with Transformers:
# Load model directly from transformers import AutoProcessor, HubertForSpeechClassification processor = AutoProcessor.from_pretrained("RamiEbeid/hubert-base-ser") model = HubertForSpeechClassification.from_pretrained("RamiEbeid/hubert-base-ser") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95b5711da32d7b9e628cc46610dc41ab39203fa603f54942bf1b7ea843d41f1b
- Size of remote file:
- 380 MB
- SHA256:
- 93c415faee111a9bca19308b74153c5adce608065f00338339c211d1236e1274
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