Instructions to use selinawisco/APAC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selinawisco/APAC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="selinawisco/APAC")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("selinawisco/APAC") model = AutoModelForAudioClassification.from_pretrained("selinawisco/APAC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from selinawisco/APAC: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/selinawisco/APAC/resolve/main/training_args.bin
- Command line
-
hf download hf://selinawisco/APAC/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/selinawisco/APAC/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- c1015d40352d99e00fab617082dccb557f27e5906c0f9f7a742c4342396b4e71
- Size of remote file:
- 4.03 kB
- SHA256:
- a0350378db8c8b905f960773fd3d87d7b9d15c56e93710b62e08e8b0958a0f14
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