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--- |
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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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--- |
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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] |
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