# Tissue
> [Tissue](https://github.com/psiace/tissue) is still in its early stages of development, so it may have bugs or APIs that are constantly changing.
Tissue is a Rust framework that enables effortless and efficient conversion of machine learning models into interactive, user-friendly demos. With Tissue, a few lines of code are all it takes to bring your machine learning algorithms to life with engaging visual applications.
## Features
- **Speedy Setup**: Get started with Tissue in minutes and integrate seamlessly with your existing Rust machine learning projects.
- **Interactive GUI**: Create a graphical user interface that makes your models accessible to non-technical users.
- **Rust-Powered**: Take advantage of Rust's performance and safety features to deploy machine learning models efficiently.
## Quick Start
To begin using Tissue, add it to your project's `Cargo.toml` file:
```toml
[dependencies]
tissue = "0.1.0"
```
Create an interactive demo with Tissue:
```rust
use tissue::{run, Input};
fn main() {
run(
|x: Vec<f32>| x.iter().sum(),
&[Input::Number(234.289), Input::Number(235.6)],
)
.expect("Could not run");
}
```
## Licenses
This library is licensed under either of:
* MIT license [LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT
* Apache License 2.0 [LICENSE-APACHE](LICENSE-APACHE) or https://opensource.org/licenses/Apache-2.0
at your option.
## Acknowledgements
Tissue owes much to the foundational work of [Chris McComb](https://twitter.com/ccmccomb)'s [tease](https://github.com/cmccomb/tease); its initial codebase was critical to Tissue's early development, despite tease no longer being actively maintained.
Inspired by the user-friendly interfaces of [Gradio](https://gradio.app/) and [Streamlit](https://streamlit.io/), Tissue aspires to streamline the sharing and demonstration of machine learning models within the Rust ecosystem, emulating the simplicity these tools offer.
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Embrace the power of Rust and bring the magic of your machine learning models to life with Tissue!