Audio Classification
Transformers
ONNX
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Instructions to use jacobgill37/rio-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jacobgill37/rio-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="jacobgill37/rio-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("jacobgill37/rio-model") model = AutoModelForAudioClassification.from_pretrained("jacobgill37/rio-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from jacobgill37/rio-model: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/jacobgill37/rio-model/resolve/main/training_args.bin
- Command line
-
hf download hf://jacobgill37/rio-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/jacobgill37/rio-model/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- c240178cb2d4955f394a0d5671d950e360d105ff03d82833dec20b0b2164ecd7
- Size of remote file:
- 5.3 kB
- SHA256:
- 9b11da011d0f810d62ba23aefc27900ae699f7f2766dec9303769e11080ffd5c
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