[Docs] Model_doc structure/clarity improvements (#26876)

* first batch of structure improvements for model_docs

* second batch of structure improvements for model_docs

* more structure improvements for model_docs

* more structure improvements for model_docs

* structure improvements for cv model_docs

* more structural refactoring

* addressed feedback about image processors

docs/source/en/model_doc/detr.md

@@ -41,6 +41,8 @@ baselines.*
 
 This model was contributed by [nielsr](https://huggingface.co/nielsr). The original code can be found [here](https://github.com/facebookresearch/detr).
 
+## How DETR works
+
 Here's a TLDR explaining how [`~transformers.DetrForObjectDetection`] works:
 
 First, an image is sent through a pre-trained convolutional backbone (in the paper, the authors use
@@ -79,7 +81,7 @@ where one first trains a [`~transformers.DetrForObjectDetection`] model to detec
 the mask head for 25 epochs. Experimentally, these two approaches give similar results. Note that predicting boxes is
 required for the training to be possible, since the Hungarian matching is computed using distances between boxes.
 
-Tips:
+## Usage tips
 
 - DETR uses so-called **object queries** to detect objects in an image. The number of queries determines the maximum
   number of objects that can be detected in a single image, and is set to 100 by default (see parameter
@@ -165,14 +167,6 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 
 If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.
 
-## DETR specific outputs
-
-[[autodoc]] models.detr.modeling_detr.DetrModelOutput
-
-[[autodoc]] models.detr.modeling_detr.DetrObjectDetectionOutput
-
-[[autodoc]] models.detr.modeling_detr.DetrSegmentationOutput
-
 ## DetrConfig
 
 [[autodoc]] DetrConfig
@@ -195,6 +189,14 @@ If you're interested in submitting a resource to be included here, please feel f
     - post_process_instance_segmentation
     - post_process_panoptic_segmentation
 
+## DETR specific outputs
+
+[[autodoc]] models.detr.modeling_detr.DetrModelOutput
+
+[[autodoc]] models.detr.modeling_detr.DetrObjectDetectionOutput
+
+[[autodoc]] models.detr.modeling_detr.DetrSegmentationOutput
+
 ## DetrModel
 
 [[autodoc]] DetrModel