Instructions to use anderloh/HuggingfaceTest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceTest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceTest")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceTest") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceTest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anderloh/HuggingfaceTest: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/anderloh/HuggingfaceTest/resolve/bc4292de658c32bda9f2caefb6cbbee22adcfae6/training_args.bin
- Command line
-
hf download hf://anderloh/HuggingfaceTest@bc4292de658c32bda9f2caefb6cbbee22adcfae6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/anderloh/HuggingfaceTest/resolve/bc4292de658c32bda9f2caefb6cbbee22adcfae6/training_args.bin
4.98 kB
- Xet hash:
- b3f21f28657ff2f19246d3a999580ab93ac8ee0440feeadef025d08e189af138
- Size of remote file:
- 4.98 kB
- SHA256:
- 4fa6bfe556f9d1f0d1e36a233df8af44e65bd398577c57be4b836291b64cc0a7
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