Instructions to use anton-l/distilhubert-ft-common-language with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/distilhubert-ft-common-language with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/distilhubert-ft-common-language")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anton-l/distilhubert-ft-common-language") model = AutoModelForAudioClassification.from_pretrained("anton-l/distilhubert-ft-common-language", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a45683ed2d59f537ed711418ab0031ae0aee509a26b1f515fa878dac07b49b76
- Size of remote file:
- 94.8 MB
- SHA256:
- 699cdd8b13fce2959df97b73ea8696149a450ee5cd935753b490bcf2d916a9f7
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