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:
- daec27e430ae3d7b11c19d217deb979c3009c201063fbde8e9ce4d38b1180ae3
- Size of remote file:
- 2.93 kB
- SHA256:
- 20df411cefb83430b4c12b54ffac1a36c6f4b249e05f72a2a067c8567e81239e
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