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1import torch
2from model_architecture import load_model
3from inference_example import predict
4
5# Load model
6model = load_model('final_usv_model.pth')
7
8# Predict on audio file
9result = predict('audio.wav', model)
10print(f"USV: {result['is_usv']}, Confidence: {result['confidence']:.2%}")pip install torch numpy librosa scipyfinal_usv_model.pth - Trained model weights (41.9 MB)model_architecture.py - CNN architecture definitioninference_example.py - Example inference codeconfig.json - Model configuration and metadatarequirements.txt - Python dependencies1@misc{usv_detector_prosap1_shank2,
2 title={Mouse USV Detector for ProSAP1/Shank2 Social Interactions},
3 author={Your Name},
4 year={2025},
5 publisher={Hugging Face},
6 howpublished={\url{https://huggingface.co/your-username/model-name}}
7}