Instructions to use Jainam/audio_classify_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jainam/audio_classify_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Jainam/audio_classify_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Jainam/audio_classify_v1") model = AutoModelForAudioClassification.from_pretrained("Jainam/audio_classify_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Jainam/audio_classify_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Jainam/audio_classify_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://Jainam/audio_classify_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Jainam/audio_classify_v1/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- c4cd3dd8168fe16f25336ff26f5d481642dee1631b58ef5d370f026dc5cf93b9
- Size of remote file:
- 3.52 kB
- SHA256:
- fd981068cd9494cbfb6fdd059eb72698933215868b9d4a978f9f1aac515e1c67
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