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[Doc] Move additional tips/notes to the top (vllm-project#9647)
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Signed-off-by: Tyler Michael Smith <[email protected]>
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DarkLight1337 authored and tlrmchlsmth committed Nov 23, 2024
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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
^^^^^^^^^^^^^^^^^^^^^^^^^

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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
=====================

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