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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- **Automotive Diagnostics**: Real-time engine knock detection in vehicles
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- **Engine Testing**: Quality control during engine development and testing
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- **Predictive Maintenance**: Early warning system for engine health monitoring
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- **Racing Applications**: Performance optimization and engine protection
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- Integration into OBD-II diagnostic tools
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- Embedded systems for real-time engine monitoring
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- Research and development in combustion analysis
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- Fleet management and vehicle health monitoring
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## Limitations
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- **Automotive Diagnostics**: Real-time engine knock detection in vehicles
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- **Engine Testing**: Quality control during engine development and testing
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- **Predictive Maintenance**: Early warning system for engine health monitoring
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## Limitations
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