Instructions to use mazkobot1/hubert-base-ls960-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mazkobot1/hubert-base-ls960-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mazkobot1/hubert-base-ls960-ft")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("mazkobot1/hubert-base-ls960-ft") model = AutoModelForAudioClassification.from_pretrained("mazkobot1/hubert-base-ls960-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77a61927f13d43d755e409e046e0c34e27016bf193e6724fd72aeb83e97b3b1a
- Size of remote file:
- 4.92 kB
- SHA256:
- 26c2bb29ca96f92fa5bfb74891acfb6f361223408fea51843266b5418fafa6bc
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