| 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 >= 1.3.0-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) |