Instructions to use walton98/model_out4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use walton98/model_out4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="walton98/model_out4")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("walton98/model_out4") model = AutoModelForAudioClassification.from_pretrained("walton98/model_out4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from walton98/model_out4: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/walton98/model_out4/resolve/main/training_args.bin
- Command line
-
hf download hf://walton98/model_out4/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/walton98/model_out4/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 07d2498550562cfe4e37f7a65e38f5cc081693bc3494db1ce08c14bf18ee0a4a
- Size of remote file:
- 3.96 kB
- SHA256:
- ff7b4d913fb67dca5308854e61a51c73a6bbf90a7180b78e71fad713e8cf3fa9
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