Update README.md

README.md

@@ -10,7 +10,7 @@ datasets:
 language:
 - en
 ---
-This is an NLI model based on T5-XXL that predicts a binary label (1 - Entailment, 0 - No entailment).
+This is an NLI model based on T5-XXL that predicts a binary label ('1' - Entailment, '0' - No entailment).
 
 It is trained similarly to the NLI model described in the [TRUE paper (Honovich et al, 2022)](https://arxiv.org/pdf/2204.04991.pdf), but using the following datasets instead of ANLI:
 - SNLI ([Bowman et al., 2015](https://arxiv.org/abs/1508.05326))
@@ -20,4 +20,4 @@ It is trained similarly to the NLI model described in the [TRUE paper (Honovich
 - PAWS ([Zhang et al. 2019](https://arxiv.org/abs/1904.01130))
 - VitaminC ([Schuster et al., 2021](https://arxiv.org/pdf/2103.08541.pdf))
 
-The input format for the model is: "premise: PREMISE_TEXT hypothesis:HYPOTHESIS_TEXT".
+The input format for the model is: "premise: PREMISE_TEXT hypothesis: HYPOTHESIS_TEXT".