Instructions to use Ammok/audio_classification_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammok/audio_classification_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Ammok/audio_classification_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Ammok/audio_classification_1") model = AutoModelForAudioClassification.from_pretrained("Ammok/audio_classification_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ammok/audio_classification_1: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Ammok/audio_classification_1/resolve/main/training_args.bin
- Command line
-
hf download hf://Ammok/audio_classification_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ammok/audio_classification_1/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 6447d1cf41a4d39465ffa3c2169ef1cb0b6ddffb15bd425df92f4378a8af839a
- Size of remote file:
- 3.96 kB
- SHA256:
- 56873a9c8406f0ecd969defe3a849867a551f2d3c1970f8afdbc205897442343
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