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:
- 46d091c0d1f4cfbc6a700ce97aff7af6f0b22d2abcbec629f944dfb2020c6f11
- Size of remote file:
- 3.06 kB
- SHA256:
- fd081c9c142702eef32bfee4ada80fd3b5c45c8c0d1907155a8281f8fd20d980
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