Instructions to use Rajaram1996/Hubert_emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rajaram1996/Hubert_emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Rajaram1996/Hubert_emotion")# Load model directly from transformers import AutoProcessor, HubertForSpeechClassification processor = AutoProcessor.from_pretrained("Rajaram1996/Hubert_emotion") model = HubertForSpeechClassification.from_pretrained("Rajaram1996/Hubert_emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89561a2315d940591829ca8e09e8b29c1fbbca3bd64be3a749620570ea268c43
- Size of remote file:
- 380 MB
- SHA256:
- 532e71ea91a66a6bdb5710361d7d2093d7e230bedc028ee38749f8e4d25a40c1
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