Add prefix to examples in model_doc rst (#11226)

* Add prefix to examples in model_doc rst

* Apply suggestions from code review

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

docs/source/model_doc/phobert.rst

@@ -31,23 +31,23 @@ Example of use:
 
 .. code-block::
 
-    import torch
-    from transformers import AutoModel, AutoTokenizer
+    >>> import torch
+    >>> from transformers import AutoModel, AutoTokenizer
 
-    phobert = AutoModel.from_pretrained("vinai/phobert-base")
-    tokenizer = AutoTokenizer.from_pretrained("vinai/phobert-base")
+    >>> phobert = AutoModel.from_pretrained("vinai/phobert-base")
+    >>> tokenizer = AutoTokenizer.from_pretrained("vinai/phobert-base")
 
-    # INPUT TEXT MUST BE ALREADY WORD-SEGMENTED!
-    line = "Tôi là sinh_viên trường đại_học Công_nghệ ."
+    >>> # INPUT TEXT MUST BE ALREADY WORD-SEGMENTED!
+    >>> line = "Tôi là sinh_viên trường đại_học Công_nghệ ."
 
-    input_ids = torch.tensor([tokenizer.encode(line)])
+    >>> input_ids = torch.tensor([tokenizer.encode(line)])
 
-    with torch.no_grad():
-        features = phobert(input_ids)  # Models outputs are now tuples
+    >>> with torch.no_grad():
+    ...     features = phobert(input_ids)  # Models outputs are now tuples
 
-    ## With TensorFlow 2.0+:
-    # from transformers import TFAutoModel
-    # phobert = TFAutoModel.from_pretrained("vinai/phobert-base")
+    >>> # With TensorFlow 2.0+:
+    >>> # from transformers import TFAutoModel
+    >>> # phobert = TFAutoModel.from_pretrained("vinai/phobert-base")
 
 
 The original code can be found `here <https://github.com/VinAIResearch/PhoBERT>`__.