Update README.md

README.md

@@ -12,8 +12,8 @@ license: mit
 # Model description:  deberta-v3-base-zeroshot-v2.0
 The model is designed for zero-shot classification with the Hugging Face pipeline. 
 
-The main advantage of this `...zeroshot-v2.0` series of zeroshot classifiers is that they are trained on commercially-friendly data
-and are fully commercially usable, while my older `...zeroshot-v1.1` included training data with non-commercially licenses data. 
+The main advantage of this `zeroshot-v2.0` series of models is that they are trained on commercially-friendly data
+and are fully commercially usable, while my older `zeroshot-v1.1` models included training data with non-commercially licenses data. 
 An overview of the latest zeroshot classifiers with different sizes and licenses is available in my [Zeroshot Classifier Collection](https://huggingface.co/collections/MoritzLaurer/zeroshot-classifiers-6548b4ff407bb19ff5c3ad6f).
 
 The model can do one universal classification task: determine whether a hypothesis is "true" or "not true" given a text