[CI] Fix repo consistency (#40249)

* fix

* doc

---------

Co-authored-by: Cyril Vallez <[email protected]>

Author: vasqu

src/transformers/models/ovis2/configuration_ovis2.py

@@ -18,7 +18,8 @@
 
 
 class Ovis2VisionConfig(PretrainedConfig):
-    r"""This is the configuration class to store the configuration of a [`Ovis2VisionModel`]. It is used to instantiate a
+    r"""
+    This is the configuration class to store the configuration of a [`Ovis2VisionModel`]. It is used to instantiate a
     Ovis2VisionModel model according to the specified arguments, defining the model architecture. Instantiating a configuration
     with the defaults will yield a similar configuration to that of Ovis2.
 
@@ -58,7 +59,7 @@ class Ovis2VisionConfig(PretrainedConfig):
             The standard deviation of the truncated normal initializer for initializing all weight matrices.
         tokenize_function (`str`, *optional*, defaults to `"softmax"`):
             The function used to tokenize the visual indicator tokens.
-    ```"""
+    """
 
     base_config_key = "vision_config"
 
@@ -106,7 +107,8 @@ def __init__(
 
 
 class Ovis2Config(PretrainedConfig):
-    r"""This is the configuration class to store the configuration of a [`Ovis2ForConditionalGeneration`]. It is used to instantiate a
+    r"""
+    This is the configuration class to store the configuration of a [`Ovis2ForConditionalGeneration`]. It is used to instantiate a
     Ovis2 model according to the specified arguments, defining the model architecture. Instantiating a configuration
     with the defaults will yield a similar configuration to that of Ovis2.
 
@@ -140,7 +142,8 @@ class Ovis2Config(PretrainedConfig):
 
     >>> # Accessing the model configuration
     >>> configuration = model.config
-    ```"""
+    ```
+    """
 
     model_type = "ovis2"
     sub_configs = {"text_config": Qwen2Config, "vision_config": Ovis2VisionConfig}

src/transformers/models/ovis2/modeling_ovis2.py

@@ -769,7 +769,7 @@ def get_decoder(self):
     def get_image_features(self, pixel_values: torch.FloatTensor):
         return self.model.get_image_features(pixel_values=pixel_values)
 
-    # Make modules available throught conditional class for BC
+    # Make modules available through conditional class for BC
     @property
     def language_model(self):
         return self.model.language_model