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  license: mit
 
 
 
 
 
 
 
 
 
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  license: mit
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+ language:
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+ - en
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+ library_name: adapter-transformers
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+ pipeline_tag: audio-classification
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+ tags:
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+ - code
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+ - audio
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+ - clap detection
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+ - machine learning
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+ # Model Card for Clap Detection Model
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+ ## Model Details
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+ ### Model Description
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+ This model is a deep learning-based audio classifier trained to detect claps in audio recordings. It has been developed using the PyTorch framework and utilizes the adapter-transformers library. The model can differentiate between clap sounds and background noise.
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+ ### Uses
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+ #### Direct Use
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+ The model can be directly used to detect claps in audio recordings.
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+ ### Bias, Risks, and Limitations
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+ The model may have limitations in accurately detecting claps in noisy environments or when there are overlapping sounds. It is recommended to evaluate the model's performance in various real-world scenarios.
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+ ## How to Get Started with the Model
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+ [More Information Needed]
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+ ## Training Details
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+ ### Training Data
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+ The model was trained on a dataset consisting of audio recordings containing both clap sounds and background noise.
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+ ### Evaluation
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+ [More Information Needed]
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+ ## Environmental Impact
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+ Carbon emissions and additional considerations have not been evaluated for this model.
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+ ## Technical Specifications
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+ ### Model Architecture and Objective
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+ [More Information Needed]
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+ ### Compute Infrastructure
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+ [More Information Needed]
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+ ## Citation
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+ [More Information Needed]
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+ ## Model Card Authors
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+ [Your Name or Username]
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+ ## Model Card Contact
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+ [Your Contact Information]