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 pytorch_model.bin from Jainam/audio_classify_v1: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Jainam/audio_classify_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Jainam/audio_classify_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Jainam/audio_classify_v1/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 43650276057698a47e7dfb0d2f25cdfb6ded644afec05377fe27dcacf0417613
- Size of remote file:
- 378 MB
- SHA256:
- 82a67309940b81f4bc1629d9919e728e68621c7d8e9eb7d610b699c978ddf31d
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