Instructions to use Kubex212/HUBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kubex212/HUBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Kubex212/HUBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Kubex212/HUBERT") model = AutoModelForAudioClassification.from_pretrained("Kubex212/HUBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Kubex212/HUBERT: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Kubex212/HUBERT/resolve/main/training_args.bin
- Command line
-
hf download hf://Kubex212/HUBERT/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Kubex212/HUBERT/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 2933bc6042992af8fa61bbe49d32c20c24c731f970a0c4a604b506178d18e837
- Size of remote file:
- 4.98 kB
- SHA256:
- 77c4f3fd581afe53900f39ba2cc3d9d077f2e507b2d81ccc7aed337cc732c3b7
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