Instructions to use codingaslu/Hubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codingaslu/Hubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="codingaslu/Hubert")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("codingaslu/Hubert") model = AutoModelForAudioClassification.from_pretrained("codingaslu/Hubert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from codingaslu/Hubert: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/codingaslu/Hubert/resolve/main/training_args.bin
- Command line
-
hf download hf://codingaslu/Hubert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codingaslu/Hubert/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- b368f81a723dbf6972f29b5b83ed505c7f9d52fe171e2d700f6d0b85c625ad28
- Size of remote file:
- 4.73 kB
- SHA256:
- 32951cc799e892507575220813206bfc3123087500c770be6d529bf30d6cf075
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