vllm/docs/source/models/supported_models.rst
2023-06-20 10:57:46 +08:00

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.. _supported_models:
Supported Models
================
vLLM supports a variety of generative Transformer models in `HuggingFace Transformers <https://huggingface.co/models>`_.
The following is the list of model architectures that are currently supported by vLLM.
Alongside each architecture, we include some popular models that use it.
.. list-table::
:widths: 25 25 50
:header-rows: 1
* - Architecture
- Models
- Example HuggingFace Models
* - :code:`GPT2LMHeadModel`
- GPT-2
- :code:`gpt2`, :code:`gpt2-xl`, etc.
* - :code:`GPTNeoXForCausalLM`
- GPT-NeoX, Pythia, OpenAssistant, Dolly V2, StableLM
- :code:`EleutherAI/gpt-neox-20b`, :code:`EleutherAI/pythia-12b`, :code:`OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5`, :code:`databricks/dolly-v2-12b`, :code:`stabilityai/stablelm-tuned-alpha-7b`, etc.
* - :code:`LlamaForCausalLM`
- LLaMA, Vicuna, Alpaca, Koala, Guanaco
- :code:`openlm-research/open_llama_13b`, :code:`lmsys/vicuna-13b-v1.3`, :code:`young-geng/koala`, :code:`JosephusCheung/Guanaco`, etc.
* - :code:`OPTForCausalLM`
- OPT, OPT-IML
- :code:`facebook/opt-66b`, :code:`facebook/opt-iml-max-30b`, etc.
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>` for instructions on how to implement support for your model.
Alternatively, you can raise an issue on our `GitHub <https://github.com/WoosukKwon/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.