[Doc] Support "important" and "announcement" admonitions (#19479)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

docs/contributing/model/multimodal.md

@@ -48,8 +48,8 @@ Further update the model as follows:
             return vision_embeddings
     ```
 
-!!! warning
-        The returned `multimodal_embeddings` must be either a **3D [torch.Tensor][]** of shape `(num_items, feature_size, hidden_size)`, or a **list / tuple of 2D [torch.Tensor][]'s** of shape `(feature_size, hidden_size)`, so that `multimodal_embeddings[i]` retrieves the embeddings generated from the `i`-th multimodal data item (e.g, image) of the request.
+!!! important
+    The returned `multimodal_embeddings` must be either a **3D [torch.Tensor][]** of shape `(num_items, feature_size, hidden_size)`, or a **list / tuple of 2D [torch.Tensor][]'s** of shape `(feature_size, hidden_size)`, so that `multimodal_embeddings[i]` retrieves the embeddings generated from the `i`-th multimodal data item (e.g, image) of the request.
 
 - Implement [get_input_embeddings][vllm.model_executor.models.interfaces.SupportsMultiModal.get_input_embeddings] to merge `multimodal_embeddings` with text embeddings from the `input_ids`. If input processing for the model is implemented correctly (see sections below), then you can leverage the utility function we provide to easily merge the embeddings.
 
@@ -100,8 +100,8 @@ Further update the model as follows:
   ```
 
 !!! note
-      The model class does not have to be named `*ForCausalLM`.
-      Check out [the HuggingFace Transformers documentation](https://huggingface.co/docs/transformers/model_doc/auto#multimodal) for some examples.
+    The model class does not have to be named `*ForCausalLM`.
+    Check out [the HuggingFace Transformers documentation](https://huggingface.co/docs/transformers/model_doc/auto#multimodal) for some examples.
 
 ## 2. Specify processing information
 

docs/contributing/model/registration.md

@@ -18,7 +18,7 @@ After you have implemented your model (see [tutorial][new-model-basic]), put it
 Then, add your model class to `_VLLM_MODELS` in <gh-file:vllm/model_executor/models/registry.py> so that it is automatically registered upon importing vLLM.
 Finally, update our [list of supported models][supported-models] to promote your model!
 
-!!! warning
+!!! important
     The list of models in each section should be maintained in alphabetical order.
 
 ## Out-of-tree models
@@ -49,6 +49,6 @@ def register():
     )
 ```
 
-!!! warning
+!!! important
     If your model is a multimodal model, ensure the model class implements the [SupportsMultiModal][vllm.model_executor.models.interfaces.SupportsMultiModal] interface.
     Read more about that [here][supports-multimodal].

docs/contributing/model/tests.md

@@ -15,7 +15,7 @@ Without them, the CI for your PR will fail.
 Include an example HuggingFace repository for your model in <gh-file:tests/models/registry.py>.
 This enables a unit test that loads dummy weights to ensure that the model can be initialized in vLLM.
 
-!!! warning
+!!! important
     The list of models in each section should be maintained in alphabetical order.
 
 !!! tip