Add and list supported models in README

README.md

@@ -39,6 +39,13 @@ vLLM is flexible and easy to use with:
 - Streaming outputs
 - OpenAI-compatible API server
 
+vLLM seamlessly supports many Huggingface models, including the following architectures:
+
+- GPT-2 (e.g., `gpt2`, `gpt2-xl`, etc.)
+- GPTNeoX (e.g., `EleutherAI/gpt-neox-20b`, `databricks/dolly-v2-12b`, `stabilityai/stablelm-tuned-alpha-7b`, etc.)
+- LLaMA (e.g., `lmsys/vicuna-13b-v1.3`, `young-geng/koala`, `openlm-research/open_llama_13b`, etc.)
+- OPT (e.g., `facebook/opt-66b`, `facebook/opt-iml-max-30b`, etc.)
+
 Install vLLM with pip or [from source](https://llm-serving-cacheflow.readthedocs-hosted.com/en/latest/getting_started/installation.html#build-from-source):
 
 ```bash

docs/source/conf.py

@@ -53,7 +53,9 @@
 #
 html_title = project
 html_theme = 'sphinx_book_theme'
+html_logo = 'assets/logos/vllm-logo-text-light.png'
 html_theme_options = {
+    'logo_only': True,
     'path_to_docs': 'docs/source',
     'repository_url': 'https://github.com/WoosukKwon/vllm',
     'use_repository_button': True,

docs/source/models/supported_models.rst

@@ -8,19 +8,24 @@ The following is the list of model architectures that are currently supported by
 Alongside each architecture, we include some popular models that use it.
 
 .. list-table::
-  :widths: 25 75
+  :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.