Instructions to use gokuls/hubert-base-ls960-finetuned-ic-slurp-wt_init with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gokuls/hubert-base-ls960-finetuned-ic-slurp-wt_init with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="gokuls/hubert-base-ls960-finetuned-ic-slurp-wt_init")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("gokuls/hubert-base-ls960-finetuned-ic-slurp-wt_init") model = AutoModelForAudioClassification.from_pretrained("gokuls/hubert-base-ls960-finetuned-ic-slurp-wt_init") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09393267378022753dee8f16f34d7112649352bc379ce2aa86c337be995f6f39
- Size of remote file:
- 4.79 kB
- SHA256:
- 2631266cd093034669a5f7af7d4342128aee5efc52f976321a31ca052f6f752a
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