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  short_description: An agent for splitting song stems
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  short_description: An agent for splitting song stems
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  ---
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+ # Music Stem Splitter
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+ This Streamlit application separates music tracks into individual stems (vocals, drums, bass, and other instruments) using the Demucs AI model.
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+ ![Music Stem Splitter Screenshot](https://huggingface.co/spaces/username/music-stem-splitter/resolve/main/screenshot.png)
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+ ## Features
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+
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+ - Upload MP3, WAV, FLAC, or OGG audio files
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+ - Separate audio into four stems: vocals, drums, bass, and other instruments
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+ - Listen to separated stems directly in the browser
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+ - View spectrograms for each stem
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+ - Download individual stems for further use
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+
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+ ## Demo
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+ 1. Upload an audio file using the file uploader
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+ 2. Click "Split into Stems" to process the audio
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+ 3. Navigate through the tabs to listen to each stem
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+ 4. Download stems individually with the provided links
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+
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+ ## Technical Details
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+ This application uses the Demucs v4 model (HT-Demucs) developed by Facebook AI Research to perform music source separation. The model leverages deep neural networks to identify and isolate different components of a music recording.
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+ ### Limitations
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+ Due to Hugging Face Spaces resource constraints:
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+ - Maximum file size: 100MB
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+ - Maximum audio duration: 5 minutes
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+ - Processing may take several minutes depending on server load
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+
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+ ### Local Installation
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+ To run this application locally:
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+ ```
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+ git clone https://huggingface.co/spaces/username/music-stem-splitter
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+ cd music-stem-splitter
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+ pip install -r requirements.txt
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+ streamlit run app.py
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+ ```
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+
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+ ## Credits
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+ - [Demucs](https://github.com/facebookresearch/demucs) by Facebook AI Research
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+ - Built with [Streamlit](https://streamlit.io/)
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+ - Hosted on [Hugging Face Spaces](https://huggingface.co/spaces)