Instructions to use halley1812/whisper-tiny-question-clf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halley1812/whisper-tiny-question-clf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="halley1812/whisper-tiny-question-clf")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("halley1812/whisper-tiny-question-clf") model = AutoModelForAudioClassification.from_pretrained("halley1812/whisper-tiny-question-clf", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from halley1812/whisper-tiny-question-clf: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/halley1812/whisper-tiny-question-clf/resolve/main/training_args.bin
- Command line
-
hf download hf://halley1812/whisper-tiny-question-clf/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/halley1812/whisper-tiny-question-clf/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 87b57bfb1a8ef8e74c39ef2fe2d0a5fac772c757602c7347b2c23b021972ebd1
- Size of remote file:
- 5.24 kB
- SHA256:
- 2cbe4c4f240a02ae84e1e3547f1e27f4fc5d1e14359d7c66de6834aa982ec681
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