Instructions to use Juardo/bsc_ai_thesis_torgo_model-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Juardo/bsc_ai_thesis_torgo_model-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Juardo/bsc_ai_thesis_torgo_model-1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Juardo/bsc_ai_thesis_torgo_model-1") model = AutoModelForAudioClassification.from_pretrained("Juardo/bsc_ai_thesis_torgo_model-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Juardo/bsc_ai_thesis_torgo_model-1: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/Juardo/bsc_ai_thesis_torgo_model-1/resolve/main/training_args.bin
- Command line
-
hf download hf://Juardo/bsc_ai_thesis_torgo_model-1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Juardo/bsc_ai_thesis_torgo_model-1/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 9a4f96b323da79db519c9f33fad0dd89f5f9804cbb92f2b48d83861bff7e01a8
- Size of remote file:
- 3.64 kB
- SHA256:
- 885f88c919a9368351db49931e2ef81dc0f0be99e5efddd11dcc13c1f2245f1c
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