update readme to mention add_special_tokens more clearly in example

README.md

@@ -93,7 +93,7 @@ for model_class, tokenizer_class, pretrained_weights in MODELS:
     model = model_class.from_pretrained(pretrained_weights)
 
     # Encode text
-    input_ids = torch.tensor([tokenizer.encode("Here is some text to encode")])
+    input_ids = torch.tensor([tokenizer.encode("Here is some text to encode", add_special_tokens=True)])  # Add special tokens takes care of adding [CLS], [SEP], <s>... tokens in the right way for each model.
     with torch.no_grad():
         last_hidden_states = model(input_ids)[0]  # Models outputs are now tuples