[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/xlm-v.md

@@ -35,7 +35,10 @@ a multilingual language model with a one million token vocabulary. XLM-V outperf
 tested on ranging from natural language inference (XNLI), question answering (MLQA, XQuAD, TyDiQA), and
 named entity recognition (WikiAnn) to low-resource tasks (Americas NLI, MasakhaNER).*
 
-Tips:
+This model was contributed by [stefan-it](https://huggingface.co/stefan-it), including detailed experiments with XLM-V on downstream tasks.
+The experiments repository can be found [here](https://github.com/stefan-it/xlm-v-experiments).
+
+## Usage tips
 
 - XLM-V is compatible with the XLM-RoBERTa model architecture, only model weights from [`fairseq`](https://github.com/facebookresearch/fairseq)
   library had to be converted.
@@ -43,5 +46,7 @@ Tips:
 
 A XLM-V (base size) model is available under the [`facebook/xlm-v-base`](https://huggingface.co/facebook/xlm-v-base) identifier.
 
-This model was contributed by [stefan-it](https://huggingface.co/stefan-it), including detailed experiments with XLM-V on downstream tasks.
-The experiments repository can be found [here](https://github.com/stefan-it/xlm-v-experiments).
+<Tip>
+
+XLM-V architecture is the same as XLM-RoBERTa, refer to [XLM-RoBERTa documentation](xlm-roberta) for API reference, and examples.
+</Tip>