Update README.md

model_cards/facebook/rag-token-nq/README.md

@@ -14,12 +14,9 @@ retriever = RagRetriever.from_pretrained("facebook/rag-token-nq", index_name="ex
 model = RagTokenForGeneration.from_pretrained("facebook/rag-token-nq", retriever=retriever)
 
 input_dict = tokenizer.prepare_seq2seq_batch("How many people live in Paris?", "In Paris, there are 10 million people.", return_tensors="pt")
-outputs = model(input_ids=input_dict["input_ids"], labels=input_dict["labels"])
-
-# outputs.loss should give 76.1230
 
 generated = model.generate(input_ids=input_dict["input_ids"])
-generated_string = tokenizer.batch_decode(generated, skip_special_tokens=True)
+print(tokenizer.batch_decode(generated, skip_special_tokens=True)[0])
 
-# generated_string should give 270,000 -> not quite correct the answer, but it also only uses a dummy index
+# generated_string should give 270,000,000 -> a bit too many I think
 ```