Instructions to use Shreeyut/Audio-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shreeyut/Audio-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Shreeyut/Audio-Classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Shreeyut/Audio-Classification") model = AutoModelForAudioClassification.from_pretrained("Shreeyut/Audio-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Shreeyut/Audio-Classification: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Shreeyut/Audio-Classification/resolve/main/model.safetensors
- Command line
-
hf download hf://Shreeyut/Audio-Classification/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Shreeyut/Audio-Classification/resolve/main/model.safetensors
378 MB
- Xet hash:
- 2364382749b6c698b77477ad43c7a2f6277b970992e9392ba85f35fab2a534ea
- Size of remote file:
- 378 MB
- SHA256:
- 29a74bfac40e51c34038d2a8098036a97c926475723d3bf9f60b853081b573ac
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