Update README.md

README.md

@@ -9,8 +9,7 @@ library_name: transformers
 license: mit
 ---
 
-# deberta-v3-large-zeroshot-v1.1-all-33
-## Model description
+## Model description: deberta-v3-large-zeroshot-v1.1-all-33
 The model is designed for zero-shot classification with the Hugging Face pipeline. 
 
 The model can do one universal task: determine whether a hypothesis is `true` or `not_true`
@@ -30,6 +29,7 @@ The model was trained on a mixture of 33 datasets and 389 classes that have been
 'agnews', 'yahootopics',
 'trueteacher', 'spam', 'wellformedquery',
 'manifesto', 'capsotu'.
+
 See details on each dataset here: https://github.com/MoritzLaurer/zeroshot-classifier/blob/main/datasets_overview.csv
 
 Note that compared to other NLI models, this model predicts two classes (`entailment` vs. `not_entailment`)