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feat: add link to colab in about and readme (#4)
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fabiogra authored Jul 16, 2023
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5 changes: 3 additions & 2 deletions README.md
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<h2 align="center">Moseca</h1>
<p align="center">Music Source Separation & Karaoke</p>


</a>
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ODoK3VXajprNbskqy7G8P1h-Zom92TMA?usp=sharing)
<a href="https://huggingface.co/spaces/fabiogra/moseca">
<img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue"
alt="Hugging Face Spaces"></a>
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[![Docker Call](https://img.shields.io/badge/-Docker%20Image-blue?logo=docker&labelColor=white)](https://huggingface.co/spaces/fabiogra/moseca/discussions?docker=true)
in just one click.

You can also speed up the music separation process by [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ODoK3VXajprNbskqy7G8P1h-Zom92TMA?usp=sharing) with GPU support.

<br>

### Open-Source and Free
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13 changes: 10 additions & 3 deletions app/pages/About.py
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<img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue"
alt="Hugging Face Spaces"></a> or locally with </font>
[![Docker Call](https://img.shields.io/badge/-Docker%20Image-blue?logo=docker&labelColor=white)](https://huggingface.co/spaces/fabiogra/moseca/discussions?docker=true)
<font size="3"> in just one click. </font>
<font size="3"> in just one click.
Speed up the music separation process with ready-to-use
[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ODoK3VXajprNbskqy7G8P1h-Zom92TMA?usp=sharing)
with GPU support.</font>
<br>
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### Are there any limitations?
<font size="3">Yes, in this environment there are some limitations regarding lenght processing
and CPU usage to allow a smooth experience for all users.
<b>If you want to remove these limitations you can deploy a Moseca app in your personal
environment like in the <a href="https://huggingface.co/spaces/fabiogra/moseca?duplicate=true"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue" alt="Hugging Face Spaces"></a> or locally with [![Docker Call](https://img.shields.io/badge/-Docker%20Image-blue?logo=docker&labelColor=white)](https://huggingface.co/spaces/fabiogra/moseca/discussions?docker=true)
<b>If you want to <u>remove these limitations</u> you can deploy a Moseca app in your personal
environment like in the <a href="https://huggingface.co/spaces/fabiogra/moseca?duplicate=true"><img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Spaces-blue" alt="Hugging Face Spaces"></a> or locally with [![Docker Call](https://img.shields.io/badge/-Docker%20Image-blue?logo=docker&labelColor=white)](https://huggingface.co/spaces/fabiogra/moseca/discussions?docker=true)</b>
You can also speed up the music separation process by [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1ODoK3VXajprNbskqy7G8P1h-Zom92TMA?usp=sharing) with GPU support.</b>
</font>
### How does Moseca work?
<font size="3"> Moseca utilizes the Hybrid Spectrogram and Waveform Source Separation ([DEMUCS](https://github.com/facebookresearch/demucs)) model from Facebook. For fast karaoke vocal removal, Moseca uses the AI vocal remover developed by [tsurumeso](https://github.com/tsurumeso/vocal-remover).
</font>
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