Shorten example width to fit in screen better

README.md

@@ -25,10 +25,16 @@ You can use the model straight from the hub but because it contains a custom for
 ```
 from transformers import AutoModel, AutoTokenizer
 
-tokenizer = AutoTokenizer.from_pretrained("Wellcome/WellcomeBertMesh")
-model = AutoModel.from_pretrained("Wellcome/WellcomeBertMesh", trust_remote_code=True)
-
-inputs = tokenizer(["This grant is about malaria and not about HIV."], padding="max_length")
+tokenizer = AutoTokenizer.from_pretrained(
+  "Wellcome/WellcomeBertMesh"
+)
+model = AutoModel.from_pretrained(
+  "Wellcome/WellcomeBertMesh",
+  trust_remote_code=True
+)
+
+text = "This grant is about malaria and not about HIV."
+inputs = tokenizer([text], padding="max_length")
 labels = model(**inputs, return_labels=True)
 print(labels)
 ```