Instructions to use Zarakun/tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zarakun/tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Zarakun/tmp")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Zarakun/tmp") model = AutoModelForAudioClassification.from_pretrained("Zarakun/tmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Zarakun/tmp: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Zarakun/tmp/resolve/main/training_args.bin
- Command line
-
hf download hf://Zarakun/tmp/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Zarakun/tmp/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- c4afec81dfa9dfb33acc1c1b3889ffadc75d25a9c2c5a0de2c842d3df35599d9
- Size of remote file:
- 5.18 kB
- SHA256:
- 7e5114e89c505e825ee20b6ad11ac1fa8a114c0e8ac937290e91a956156b46fd
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