gradio/guides/readme_template.md
Abubakar Abid 4bee781da4
Guides Section and Redesign Parts of the Website (#490)
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Co-authored-by: Abubakar Abid <aaabid93@gmail.com>
Co-authored-by: Abubakar Abid <a12d@stanford.edu>
Co-authored-by: aliabd <ali.si3luwa@gmail.com>
2022-02-05 01:42:49 +04:00

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# Welcome to Gradio
Quickly create beautiful user interfaces around your machine learning models. Gradio (pronounced GRAY-dee-oh) makes it easy for you to demo your model in your browser or let people "try it out" by dragging-and-dropping in their own images, pasting text, recording their own voice, etc. and seeing what the model outputs.
![Interface montage](website/homepage/src/assets/img/montage.gif)
Gradio is useful for:
* **Demoing** your machine learning models for clients / collaborators / users / students
* **Deploying** your models quickly with automatic shareable links and getting feedback on model performance
* **Debugging** your model interactively during development using built-in manipulation and interpretation tools
**You can find an interactive version of the following Getting Started at [https://gradio.app/getting_started](https://gradio.app/getting_started).**
{% with code=code, demos=demos %}
{% include "getting_started.md" %}
{% endwith %}
## System Requirements:
Gradio requires Python `3.7+` and has been tested on the latest versions of Windows, MacOS, and various common Linux distributions (e.g. Ubuntu). For Python package requirements, please see the `setup.py` file.
## Contributing:
If you would like to contribute and your contribution is small, you can directly open a pull request (PR). If you would like to contribute a larger feature, we recommend first creating an issue with a proposed design for discussion. Please see our [contributing guidelines](https://github.com/gradio-app/gradio/blob/master/CONTRIBUTING.md) for more info.
## License:
Gradio is licensed under the Apache License 2.0
## See more:
You can find many more examples as well as more info on usage on our website: www.gradio.app
See, also, the accompanying paper: ["Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild"](https://arxiv.org/pdf/1906.02569.pdf), *ICML HILL 2019*, and please use the citation below.
```
@article{abid2019gradio,
title={Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild},
author={Abid, Abubakar and Abdalla, Ali and Abid, Ali and Khan, Dawood and Alfozan, Abdulrahman and Zou, James},
journal={arXiv preprint arXiv:1906.02569},
year={2019}
}
```