Docs: Fix broken cross-references, i.e. ~transformer. -> ~transformers. (#27740)

~transformer. -> ~transformers.

docs/source/en/model_doc/auto.md

@@ -49,7 +49,7 @@ You will then be able to use the auto classes like you would usually do!
 
 <Tip warning={true}>
 
-If your `NewModelConfig` is a subclass of [`~transformer.PretrainedConfig`], make sure its
+If your `NewModelConfig` is a subclass of [`~transformers.PretrainedConfig`], make sure its
 `model_type` attribute is set to the same key you use when registering the config (here `"new-model"`).
 
 Likewise, if your `NewModel` is a subclass of [`PreTrainedModel`], make sure its

docs/source/ja/model_doc/auto.md

@@ -43,7 +43,7 @@ AutoModel.register(NewModelConfig, NewModel)
 
 <Tip warning={true}>
 
-あなたの`NewModelConfig`が[`~transformer.PretrainedConfig`]のサブクラスである場合、その`model_type`属性がコンフィグを登録するときに使用するキー（ここでは`"new-model"`）と同じに設定されていることを確認してください。
+あなたの`NewModelConfig`が[`~transformers.PretrainedConfig`]のサブクラスである場合、その`model_type`属性がコンフィグを登録するときに使用するキー（ここでは`"new-model"`）と同じに設定されていることを確認してください。
 
 同様に、あなたの`NewModel`が[`PreTrainedModel`]のサブクラスである場合、その`config_class`属性がモデルを登録する際に使用するクラス（ここでは`NewModelConfig`）と同じに設定されていることを確認してください。
 

src/transformers/generation/beam_search.py

@@ -151,7 +151,7 @@ class BeamSearchScorer(BeamScorer):
             beam search algorithm).
         num_beam_hyps_to_keep (`int`, *optional*, defaults to 1):
             The number of beam hypotheses that shall be returned upon calling
-            [`~transformer.BeamSearchScorer.finalize`].
+            [`~transformers.BeamSearchScorer.finalize`].
         num_beam_groups (`int`, *optional*, defaults to 1):
             Number of groups to divide `num_beams` into in order to ensure diversity among different groups of beams.
             See [this paper](https://arxiv.org/pdf/1610.02424.pdf) for more details.
@@ -444,7 +444,7 @@ class ConstrainedBeamSearchScorer(BeamScorer):
             beam search algorithm).
         num_beam_hyps_to_keep (`int`, *optional*, defaults to 1):
             The number of beam hypotheses that shall be returned upon calling
-            [`~transformer.BeamSearchScorer.finalize`].
+            [`~transformers.BeamSearchScorer.finalize`].
         num_beam_groups (`int`, *optional*, defaults to 1):
             Number of groups to divide `num_beams` into in order to ensure diversity among different groups of beams.
             See [this paper](https://arxiv.org/pdf/1610.02424.pdf) for more details.

src/transformers/trainer.py

@@ -650,38 +650,38 @@ class Trainer:
 
     def add_callback(self, callback):
         """
-        Add a callback to the current list of [`~transformer.TrainerCallback`].
+        Add a callback to the current list of [`~transformers.TrainerCallback`].
 
         Args:
-           callback (`type` or [`~transformer.TrainerCallback`]):
-               A [`~transformer.TrainerCallback`] class or an instance of a [`~transformer.TrainerCallback`]. In the
+           callback (`type` or [`~transformers.TrainerCallback`]):
+               A [`~transformers.TrainerCallback`] class or an instance of a [`~transformers.TrainerCallback`]. In the
                first case, will instantiate a member of that class.
         """
         self.callback_handler.add_callback(callback)
 
     def pop_callback(self, callback):
         """
-        Remove a callback from the current list of [`~transformer.TrainerCallback`] and returns it.
+        Remove a callback from the current list of [`~transformers.TrainerCallback`] and returns it.
 
         If the callback is not found, returns `None` (and no error is raised).
 
         Args:
-           callback (`type` or [`~transformer.TrainerCallback`]):
-               A [`~transformer.TrainerCallback`] class or an instance of a [`~transformer.TrainerCallback`]. In the
+           callback (`type` or [`~transformers.TrainerCallback`]):
+               A [`~transformers.TrainerCallback`] class or an instance of a [`~transformers.TrainerCallback`]. In the
                first case, will pop the first member of that class found in the list of callbacks.
 
         Returns:
-            [`~transformer.TrainerCallback`]: The callback removed, if found.
+            [`~transformers.TrainerCallback`]: The callback removed, if found.
         """
         return self.callback_handler.pop_callback(callback)
 
     def remove_callback(self, callback):
         """
-        Remove a callback from the current list of [`~transformer.TrainerCallback`].
+        Remove a callback from the current list of [`~transformers.TrainerCallback`].
 
         Args:
-           callback (`type` or [`~transformer.TrainerCallback`]):
-               A [`~transformer.TrainerCallback`] class or an instance of a [`~transformer.TrainerCallback`]. In the
+           callback (`type` or [`~transformers.TrainerCallback`]):
+               A [`~transformers.TrainerCallback`] class or an instance of a [`~transformers.TrainerCallback`]. In the
                first case, will remove the first member of that class found in the list of callbacks.
         """
         self.callback_handler.remove_callback(callback)

src/transformers/trainer_callback.py

@@ -207,7 +207,7 @@ class TrainerCallback:
 
     The argument `args`, `state` and `control` are positionals for all events, all the others are grouped in `kwargs`.
     You can unpack the ones you need in the signature of the event using them. As an example, see the code of the
-    simple [`~transformer.PrinterCallback`].
+    simple [`~transformers.PrinterCallback`].
 
     Example: