Spaces:
Sleeping
Sleeping
Fabio Grasso
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docs: update readme
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README.md
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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>
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