fix typos in idefics.md (#26648)

* fix typos in idefics.md

Two typos found in reviewing this documentation.

1) max_new_tokens=4, is not sufficient to generate "Vegetables" as indicated - you will get only "Veget". (incidentally - some mention of how to select this value might be useful as it seems to change in each example)

2) inputs = processor(prompts, return_tensors="pt").to(device) as inputs need to be on the same device (as they are in all other examples on the page)

* Update idefics.md

Change device to cuda explicitly to match other examples

docs/source/en/tasks/idefics.md

@@ -276,7 +276,7 @@ We can instruct the model to classify the image into one of the categories that
 >>> inputs = processor(prompt, return_tensors="pt").to("cuda")
 >>> bad_words_ids = processor.tokenizer(["<image>", "<fake_token_around_image>"], add_special_tokens=False).input_ids
 
->>> generated_ids = model.generate(**inputs, max_new_tokens=4, bad_words_ids=bad_words_ids)
+>>> generated_ids = model.generate(**inputs, max_new_tokens=6, bad_words_ids=bad_words_ids)
 >>> generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)
 >>> print(generated_text[0])
 Instruction: Classify the following image into a single category from the following list: ['animals', 'vegetables', 'city landscape', 'cars', 'office'].
@@ -357,7 +357,7 @@ for a batch of examples by passing a list of prompts:
 ...     ],
 ... ]
 
->>> inputs = processor(prompts, return_tensors="pt")
+>>> inputs = processor(prompts, return_tensors="pt").to("cuda")
 >>> bad_words_ids = processor.tokenizer(["<image>", "<fake_token_around_image>"], add_special_tokens=False).input_ids
 
 >>> generated_ids = model.generate(**inputs, max_new_tokens=10, bad_words_ids=bad_words_ids)