Audio Classification
Transformers
Safetensors
audio-spectrogram-transformer
vision-transformer
engine-knock-detection
automotive
audio-spectrogram
Generated from Trainer
Eval Results (legacy)
Instructions to use cxlrd/revix-AST-engine-knock with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cxlrd/revix-AST-engine-knock with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="cxlrd/revix-AST-engine-knock")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("cxlrd/revix-AST-engine-knock") model = AutoModelForAudioClassification.from_pretrained("cxlrd/revix-AST-engine-knock") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2dcf73cc75d55ca2ad0f47d5e19b0d8034db2f480c2404a805a4d21e31e494b
- Size of remote file:
- 5.84 kB
- SHA256:
- b67638d757612b6652ec88aaaaed752c9565b319729397797c32b0c8081cf768
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