Instructions to use chrisgg1/hubert-base-ls960-finetuned-ks-3s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chrisgg1/hubert-base-ls960-finetuned-ks-3s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="chrisgg1/hubert-base-ls960-finetuned-ks-3s")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("chrisgg1/hubert-base-ls960-finetuned-ks-3s") model = AutoModelForAudioClassification.from_pretrained("chrisgg1/hubert-base-ls960-finetuned-ks-3s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08629bc0a08bec951cc3a5602a81cf394e09061f47301188ace3f1ce5fb1b116
- Size of remote file:
- 4.73 kB
- SHA256:
- d4d9ac9d167f43d873fbb8f59d172c8d2b14754a4bfece6e69f7421230b4787d
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