Instructions to use BOENE/distilhubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BOENE/distilhubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="BOENE/distilhubert")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("BOENE/distilhubert") model = AutoModelForAudioClassification.from_pretrained("BOENE/distilhubert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from BOENE/distilhubert: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/BOENE/distilhubert/resolve/main/training_args.bin
- Command line
-
hf download hf://BOENE/distilhubert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/BOENE/distilhubert/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- d8e450e7637bd67276ea5ede660ea2c30df1cafcf11251e49d5e8089a9d8ab25
- Size of remote file:
- 4.66 kB
- SHA256:
- 119e7bd6914926d4fa7019ca6309f47cb91cef53dfd13a9d3043c54fc133a174
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