[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/yolos.md

@@ -25,10 +25,6 @@ The abstract from the paper is the following:
 
 *Can Transformer perform 2D object- and region-level recognition from a pure sequence-to-sequence perspective with minimal knowledge about the 2D spatial structure? To answer this question, we present You Only Look at One Sequence (YOLOS), a series of object detection models based on the vanilla Vision Transformer with the fewest possible modifications, region priors, as well as inductive biases of the target task. We find that YOLOS pre-trained on the mid-sized ImageNet-1k dataset only can already achieve quite competitive performance on the challenging COCO object detection benchmark, e.g., YOLOS-Base directly adopted from BERT-Base architecture can obtain 42.0 box AP on COCO val. We also discuss the impacts as well as limitations of current pre-train schemes and model scaling strategies for Transformer in vision through YOLOS.*
 
-Tips:
-
-- One can use [`YolosImageProcessor`] for preparing images (and optional targets) for the model. Contrary to [DETR](detr), YOLOS doesn't require a `pixel_mask` to be created.
-
 <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/yolos_architecture.png"
 alt="drawing" width="600"/>
 
@@ -47,6 +43,12 @@ 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.
 
+<Tip>
+
+Use [`YolosImageProcessor`] for preparing images (and optional targets) for the model. Contrary to [DETR](detr), YOLOS doesn't require a `pixel_mask` to be created.
+
+</Tip>
+
 ## YolosConfig
 
 [[autodoc]] YolosConfig
@@ -65,13 +67,11 @@ If you're interested in submitting a resource to be included here, please feel f
     - pad
     - post_process_object_detection
 
-
 ## YolosModel
 
 [[autodoc]] YolosModel
     - forward
 
-
 ## YolosForObjectDetection
 
 [[autodoc]] YolosForObjectDetection