Instructions to use wojtek2288/HUBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wojtek2288/HUBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="wojtek2288/HUBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("wojtek2288/HUBERT") model = AutoModelForAudioClassification.from_pretrained("wojtek2288/HUBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wojtek2288/HUBERT: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/wojtek2288/HUBERT/resolve/main/training_args.bin
- Command line
-
hf download hf://wojtek2288/HUBERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wojtek2288/HUBERT/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- c71333c8eed62fc61f13524eff3bf8c6503319f8f9a55ef6c2e112bc7f01959c
- Size of remote file:
- 4.98 kB
- SHA256:
- d7f15f5651700c77dc71d28d7ea3e0fb7a2f28788577ab5263fffb2978b03f66
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.