---
license: mit
library_name: unity-sentis
pipeline_tag: zero-shot-classification
---


# Deberta v3 zeroshot for Unity Sentis

This is the [DeBERTaV3 Model](https://huggingface.co/MoritzLaurer/deberta-v3-base-zeroshot-v1.1-all-33) in the Sentis format to run on Unity 2023.
The model can do one universal classification task: determine whether a hypothesis is "true" or "not true" given a text.

There are more models of different sizes that are compatible made by [MoritzLaurer](https://huggingface.co/MoritzLaurer)

## How to Use

* Ensure Sentis version is 1.4.0-pre.3
* Create a new scene in Unity 2023
* Add the DebertaV3.cs file to a GameObject in the scene
* Assign model and vocabulary
* Press play, the classification scores will show in the Console

# Example Inputs
```
text = "Angela Merkel is a politician in Germany and leader of the CDU"

classes = ["This example is about politics", "This example is about economy", "This example is about entertainment", "This example is about environment"]
```

# Example Outputs
```
[politics] Entailment Score: 0.9998765

[economy] Entailment Score: 0.0008297313

[entertainment] Entailment Score: 4.86502E-05

[environment] Entailment Score: 6.163981E-05
```

## Unity Sentis
Sentis is the inference engine for Unity. More can be found about it [here](https://unity.com/products/sentis)