Move additional tips/notes to the top

docs/source/models/supported_models.rst

@@ -3,10 +3,47 @@
 Supported Models
 ================
 
-vLLM supports a variety of generative Transformer models in `HuggingFace (HF) Transformers <https://huggingface.co/models>`_.
-The following is the list of model architectures that are currently supported by vLLM.
+vLLM supports a variety of generative and embedding models from `HuggingFace (HF) Transformers <https://huggingface.co/models>`_.
+This page lists the model architectures that are currently supported by vLLM.
 Alongside each architecture, we include some popular models that use it.
 
+For other models, you can check the :code:`config.json` file inside the model repository.
+If the :code:`"architectures"` field contains a model architecture listed below, then it should be supported in theory.
+
+.. tip::
+    The easiest way to check if your model is really supported at runtime is to run the program below:
+
+    .. code-block:: python
+
+        from vllm import LLM
+
+        llm = LLM(model=...)  # Name or path of your model
+        output = llm.generate("Hello, my name is")
+        print(output)
+
+    If vLLM successfully generates text, it indicates that your model is supported.
+
+Otherwise, please refer to :ref:`Adding a New Model <adding_a_new_model>` and :ref:`Enabling Multimodal Inputs <enabling_multimodal_inputs>` 
+for instructions on how to implement your model in vLLM.
+Alternatively, you can `open an issue on GitHub <https://github.com/vllm-project/vllm/issues/new/choose>`_ to request vLLM support.
+
+.. note::
+    To use models from `ModelScope <https://www.modelscope.cn>`_ instead of HuggingFace Hub, set an environment variable:
+
+    .. code-block:: shell
+
+       $ export VLLM_USE_MODELSCOPE=True
+
+    And use with :code:`trust_remote_code=True`.
+
+    .. code-block:: python
+
+        from vllm import LLM
+
+        llm = LLM(model=..., revision=..., trust_remote_code=True)  # Name or path of your model
+        output = llm.generate("Hello, my name is")
+        print(output)
+
 Text-only Language Models
 ^^^^^^^^^^^^^^^^^^^^^^^^^
 
@@ -144,7 +181,7 @@ Text Generation
     - ✅︎
   * - :code:`JAISLMHeadModel`
     - Jais
-    - :code:`inceptionai/jais-13b`, :code:`inceptionai/jais-13b-chat`, :code:`inceptionai/jais-30b-v3`, :code:`inceptionai/jais-30b-chat-v3`, etc.
+    - :code:`core42/jais-13b`, :code:`core42/jais-13b-chat`, :code:`core42/jais-30b-v3`, :code:`core42/jais-30b-chat-v3`, etc.
     -
     - ✅︎
   * - :code:`JambaForCausalLM`
@@ -425,7 +462,7 @@ Text Generation
     -
   * - :code:`MolmoForCausalLM`
     - Molmo
-    - T + I
+    - Image
     - :code:`allenai/Molmo-7B-D-0924`, :code:`allenai/Molmo-72B-0924`, etc.
     -
     - ✅︎
@@ -459,12 +496,6 @@ Text Generation
     - :code:`Qwen/Qwen-VL`, :code:`Qwen/Qwen-VL-Chat`, etc.
     -
     - ✅︎
-  * - :code:`Qwen2AudioForConditionalGeneration`
-    - Qwen2-Audio
-    - T + A\ :sup:`+`
-    - :code:`Qwen/Qwen2-Audio-7B-Instruct`
-    -
-    - ✅︎
   * - :code:`Qwen2VLForConditionalGeneration`
     - Qwen2-VL
     - T + I\ :sup:`E+` + V\ :sup:`+`
@@ -515,44 +546,6 @@ Multimodal Embedding
   Some model architectures support both generation and embedding tasks.
   In this case, you have to pass :code:`--task embedding` to run the model in embedding mode.
 
-----
-
-If your model uses one of the above model architectures, you can seamlessly run your model with vLLM.
-Otherwise, please refer to :ref:`Adding a New Model <adding_a_new_model>` and :ref:`Enabling Multimodal Inputs <enabling_multimodal_inputs>` 
-for instructions on how to implement support for your model.
-Alternatively, you can raise an issue on our `GitHub <https://github.com/vllm-project/vllm/issues>`_ project.
-
-.. tip::
-    The easiest way to check if your model is supported is to run the program below:
-
-    .. code-block:: python
-
-        from vllm import LLM
-
-        llm = LLM(model=...)  # Name or path of your model
-        output = llm.generate("Hello, my name is")
-        print(output)
-
-    If vLLM successfully generates text, it indicates that your model is supported.
-
-.. tip::
-    To use models from `ModelScope <https://www.modelscope.cn>`_ instead of HuggingFace Hub, set an environment variable:
-
-    .. code-block:: shell
-
-       $ export VLLM_USE_MODELSCOPE=True
-
-    And use with :code:`trust_remote_code=True`.
-
-    .. code-block:: python
-
-        from vllm import LLM
-
-        llm = LLM(model=..., revision=..., trust_remote_code=True)  # Name or path of your model
-        output = llm.generate("Hello, my name is")
-        print(output)
-
-
 Model Support Policy
 =====================