Instructions to use Selma323/first_dys_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Selma323/first_dys_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Selma323/first_dys_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Selma323/first_dys_model") model = AutoModelForAudioClassification.from_pretrained("Selma323/first_dys_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Selma323/first_dys_model: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Selma323/first_dys_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Selma323/first_dys_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Selma323/first_dys_model/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 31264ac59d629d50e2ef53f385df706d92a897a7c870c9002a2f8836bfe26fa6
- Size of remote file:
- 4.98 kB
- SHA256:
- 14057a2d6445eb393888d90b05df2ba9357e2e5a5ea76f602f93c85d67fc4722
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