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:
- 1b56a57201cff0982ebb287bb427ba8d4c75ae07f66145fa47834199393c20bd
- Size of remote file:
- 378 MB
- SHA256:
- b83c5e9ef52ccb0eaf4dc75b0e57d6f0d24aea111780f82ce8f4fd0d23bd51e3
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