Instructions to use Anguuuuus/laryngitis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anguuuuus/laryngitis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Anguuuuus/laryngitis")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Anguuuuus/laryngitis") model = AutoModelForAudioClassification.from_pretrained("Anguuuuus/laryngitis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Anguuuuus/laryngitis: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/Anguuuuus/laryngitis/resolve/main/training_args.bin
- Command line
-
hf download hf://Anguuuuus/laryngitis/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Anguuuuus/laryngitis/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- c3eb816fcfd41115ef38ad37c2d322995d7542453048f55eae0191062f47f9e0
- Size of remote file:
- 4.6 kB
- SHA256:
- 726c680b4bbe45a69dfefa5ae6c9b13640e2492ae3acc5739c2015747319c1cf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.