[LED] Correct Docs (#10419)

* correct docs

* correct tf model docs as well

src/transformers/models/led/modeling_led.py

@@ -1516,8 +1516,17 @@ LED_INPUTS_DOCSTRING = r"""
 
             `What are attention masks? <../glossary.html#attention-mask>`__
         decoder_input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`):
-            Provide for translation and summarization training. By default, the model will create this tensor by
-            shifting the :obj:`input_ids` to the right, following the paper.
+            Indices of decoder input sequence tokens in the vocabulary.
+
+            Indices can be obtained using :class:`~transformers.LedTokenizer`. See
+            :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for
+            details.
+
+            `What are input IDs? <../glossary.html#input-ids>`__
+
+            LED uses the :obj:`eos_token_id` as the starting token for :obj:`decoder_input_ids` generation. If
+            :obj:`past_key_values` is used, optionally only the last :obj:`decoder_input_ids` have to be input (see
+            :obj:`past_key_values`).
         decoder_attention_mask (:obj:`torch.LongTensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`):
             Default behavior: generate a tensor that ignores pad tokens in :obj:`decoder_input_ids`. Causal mask will
             also be used by default.

src/transformers/models/led/modeling_tf_led.py

@@ -1533,9 +1533,18 @@ LED_INPUTS_DOCSTRING = r"""
             - 0 for tokens that are **masked**.
 
             `What are attention masks? <../glossary.html#attention-mask>`__
-        decoder_input_ids (:obj:`tf.Tensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`):
-            Provide for translation and summarization training. By default, the model will create this tensor by
-            shifting the input_ids right, following the paper.
+        decoder_input_ids (:obj:`tf.LongTensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`):
+            Indices of decoder input sequence tokens in the vocabulary.
+
+            Indices can be obtained using :class:`~transformers.LedTokenizer`. See
+            :meth:`transformers.PreTrainedTokenizer.encode` and :meth:`transformers.PreTrainedTokenizer.__call__` for
+            details.
+
+            `What are input IDs? <../glossary.html#input-ids>`__
+
+            LED uses the :obj:`eos_token_id` as the starting token for :obj:`decoder_input_ids` generation. If
+            :obj:`past_key_values` is used, optionally only the last :obj:`decoder_input_ids` have to be input (see
+            :obj:`past_key_values`).
         decoder_attention_mask (:obj:`tf.Tensor` of shape :obj:`(batch_size, target_sequence_length)`, `optional`):
             will be made by default and ignore pad tokens. It is not recommended to set this for most use cases.
         head_mask (:obj:`tf.Tensor` of shape :obj:`(encoder_layers, encoder_attention_heads)`, `optional`):