Instructions to use vpingale07/distilhubert-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vpingale07/distilhubert-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="vpingale07/distilhubert-v2")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("vpingale07/distilhubert-v2") model = AutoModelForAudioClassification.from_pretrained("vpingale07/distilhubert-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 179e7e46913550b1002dec32022a187520c6e4f612a14daa5eaf252845eedfbc
- Size of remote file:
- 4.92 kB
- SHA256:
- e70c50333acea8d4fee5e58dd636771050cfcb8e90400b19c109b2f47da202b4
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