Fabio Grasso commited on
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docs: update readme

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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+ # Music Source Splitter 🎶
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+ <a href="https://huggingface.co/spaces/fabiogra/st-music-splitter"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue" alt="Hugging Face Spaces"></a>
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+ This is a streamlit demo of the [Music Source Separation](https://huggingface.co/spaces/fabiogra/st-music-splitter).
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+ The model can separate the vocals, drums, bass, and other from a music track.
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+ ## Usage
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+ You can use the demo [here](https://huggingface.co/spaces/fabiogra/st-music-splitter), or run it locally with:
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+ ```bash
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+ streamlit run app.py
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+ ```
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+ > **Note**: In order to run the demo locally, you need to install the dependencies with `pip install -r requirements.txt`.
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+ ## How it works
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+ The app uses a pretrained model called Hybrid Spectrogram and Waveform Source Separation from <a href="https://github.com/facebookresearch/demucs">facebook/htdemucs</a>.
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+ ## Acknowledgements
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+ - HtDemucs model from <a href="https://github.com/facebookresearch/demucs">facebook/htdemucs</a>
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+ - Streamlit Audio Recorder from <a href="https://github.com/stefanrmmr/streamlit_audio_recorder">stefanrmmr/streamlit_audio_recorder</a>