[tokenizer.prepare_seq2seq_batch] change deprecation to be easily actionable (#12669)

* change deprecation to be easily actionable

* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* rework as suggested

* one warning together

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

src/transformers/tokenization_utils_base.py

@@ -3274,13 +3274,23 @@ class PreTrainedTokenizerBase(SpecialTokensMixin, PushToHubMixin):
             The full set of keys ``[input_ids, attention_mask, labels]``, will only be returned if tgt_texts is passed.
             Otherwise, input_ids, attention_mask will be the only keys.
         """
-        warnings.warn(
-            "`prepare_seq2seq_batch` is deprecated and will be removed in version 5 of 🤗 Transformers. Use the "
-            "regular `__call__` method to prepare your inputs and the tokenizer under the `as_target_tokenizer` "
-            "context manager to prepare your targets. See the documentation of your specific tokenizer for more "
-            "details",
-            FutureWarning,
-        )
+        # docstyle-ignore
+        formatted_warning = """
+`prepare_seq2seq_batch` is deprecated and will be removed in version 5 of HuggingFace Transformers. Use the regular
+`__call__` method to prepare your inputs and the tokenizer under the `as_target_tokenizer` context manager to prepare
+your targets.
+
+Here is a short example:
+
+model_inputs = tokenizer(src_texts, ...)
+with tokenizer.as_target_tokenizer():
+    labels = tokenizer(tgt_texts, ...)
+model_inputs["labels"] = labels["input_ids"]
+
+See the documentation of your specific tokenizer for more details on the specific arguments to the tokenizer of choice.
+For a more complete example, see the implementation of `prepare_seq2seq_batch`.
+"""
+        warnings.warn(formatted_warning, FutureWarning)
         # mBART-specific kwargs that should be ignored by other models.
         kwargs.pop("src_lang", None)
         kwargs.pop("tgt_lang", None)