[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/regnet.md

@@ -26,15 +26,13 @@ The abstract from the paper is the following:
 
 *In this work, we present a new network design paradigm. Our goal is to help advance the understanding of network design and discover design principles that generalize across settings. Instead of focusing on designing individual network instances, we design network design spaces that parametrize populations of networks. The overall process is analogous to classic manual design of networks, but elevated to the design space level. Using our methodology we explore the structure aspect of network design and arrive at a low-dimensional design space consisting of simple, regular networks that we call RegNet. The core insight of the RegNet parametrization is surprisingly simple: widths and depths of good networks can be explained by a quantized linear function. We analyze the RegNet design space and arrive at interesting findings that do not match the current practice of network design. The RegNet design space provides simple and fast networks that work well across a wide range of flop regimes. Under comparable training settings and flops, the RegNet models outperform the popular EfficientNet models while being up to 5x faster on GPUs.*
 
-Tips:
-
-- One can use [`AutoImageProcessor`] to prepare images for the model.
-- The huge 10B model from [Self-supervised Pretraining of Visual Features in the Wild](https://arxiv.org/abs/2103.01988), trained on one billion Instagram images, is available on the [hub](https://huggingface.co/facebook/regnet-y-10b-seer)
-
 This model was contributed by [Francesco](https://huggingface.co/Francesco). The TensorFlow version of the model
 was contributed by [sayakpaul](https://huggingface.com/sayakpaul) and [ariG23498](https://huggingface.com/ariG23498).
 The original code can be found [here](https://github.com/facebookresearch/pycls).
 
+The huge 10B model from [Self-supervised Pretraining of Visual Features in the Wild](https://arxiv.org/abs/2103.01988), 
+trained on  one billion Instagram images, is available on the [hub](https://huggingface.co/facebook/regnet-y-10b-seer)
+
 ## Resources
 
 A list of official Hugging Face and community (indicated by 🌎) resources to help you get started with RegNet.
@@ -50,37 +48,43 @@ If you're interested in submitting a resource to be included here, please feel f
 
 [[autodoc]] RegNetConfig
 
+<frameworkcontent>
+<pt>
 
 ## RegNetModel
 
 [[autodoc]] RegNetModel
     - forward
 
-
 ## RegNetForImageClassification
 
 [[autodoc]] RegNetForImageClassification
     - forward
 
+</pt>
+<tf>
+
 ## TFRegNetModel
 
 [[autodoc]] TFRegNetModel
     - call
 
-
 ## TFRegNetForImageClassification
 
 [[autodoc]] TFRegNetForImageClassification
     - call
 
+</tf>
+<jax>
 
 ## FlaxRegNetModel
 
 [[autodoc]] FlaxRegNetModel
     - __call__
 
-
 ## FlaxRegNetForImageClassification
 
 [[autodoc]] FlaxRegNetForImageClassification
-    - __call__
+    - __call__
+</jax>
+</frameworkcontent>