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[docs] Add LoRA support information for models #3299

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3 changes: 2 additions & 1 deletion docs/source/models/lora.rst
Original file line number Diff line number Diff line change
Expand Up @@ -92,7 +92,8 @@ LoRA adapter requests if they were provided and ``max_loras`` is set high enough

The following is an example request

.. code-block::bash
.. code-block:: bash

curl http://localhost:8000/v1/completions \
-H "Content-Type: application/json" \
-d '{
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27 changes: 26 additions & 1 deletion docs/source/models/supported_models.rst
Original file line number Diff line number Diff line change
Expand Up @@ -8,84 +8,109 @@ 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 25 50
:widths: 25 25 50 5
:header-rows: 1

* - Architecture
- Models
- Example HuggingFace Models
- :ref:`LoRA <lora>`
* - :code:`AquilaForCausalLM`
- Aquila
- :code:`BAAI/Aquila-7B`, :code:`BAAI/AquilaChat-7B`, etc.
- ✅︎
* - :code:`BaiChuanForCausalLM`
- Baichuan
- :code:`baichuan-inc/Baichuan2-13B-Chat`, :code:`baichuan-inc/Baichuan-7B`, etc.
-
* - :code:`ChatGLMModel`
- ChatGLM
- :code:`THUDM/chatglm2-6b`, :code:`THUDM/chatglm3-6b`, etc.
-
* - :code:`DeciLMForCausalLM`
- DeciLM
- :code:`Deci/DeciLM-7B`, :code:`Deci/DeciLM-7B-instruct`, etc.
-
* - :code:`BloomForCausalLM`
- BLOOM, BLOOMZ, BLOOMChat
- :code:`bigscience/bloom`, :code:`bigscience/bloomz`, etc.
-
* - :code:`FalconForCausalLM`
- Falcon
- :code:`tiiuae/falcon-7b`, :code:`tiiuae/falcon-40b`, :code:`tiiuae/falcon-rw-7b`, etc.
-
* - :code:`GemmaForCausalLM`
- Gemma
- :code:`google/gemma-2b`, :code:`google/gemma-7b`, etc.
- ✅︎
* - :code:`GPT2LMHeadModel`
- GPT-2
- :code:`gpt2`, :code:`gpt2-xl`, etc.
-
* - :code:`GPTBigCodeForCausalLM`
- StarCoder, SantaCoder, WizardCoder
- :code:`bigcode/starcoder`, :code:`bigcode/gpt_bigcode-santacoder`, :code:`WizardLM/WizardCoder-15B-V1.0`, etc.
-
* - :code:`GPTJForCausalLM`
- GPT-J
- :code:`EleutherAI/gpt-j-6b`, :code:`nomic-ai/gpt4all-j`, 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:`InternLMForCausalLM`
- InternLM
- :code:`internlm/internlm-7b`, :code:`internlm/internlm-chat-7b`, etc.
- ✅︎
* - :code:`InternLM2ForCausalLM`
- InternLM2
- :code:`internlm/internlm2-7b`, :code:`internlm/internlm2-chat-7b`, etc.
-
* - :code:`LlamaForCausalLM`
- LLaMA, LLaMA-2, Vicuna, Alpaca, Yi
- :code:`meta-llama/Llama-2-13b-hf`, :code:`meta-llama/Llama-2-70b-hf`, :code:`openlm-research/open_llama_13b`, :code:`lmsys/vicuna-13b-v1.3`, :code:`01-ai/Yi-6B`, :code:`01-ai/Yi-34B`, etc.
- ✅︎
* - :code:`MistralForCausalLM`
- Mistral, Mistral-Instruct
- :code:`mistralai/Mistral-7B-v0.1`, :code:`mistralai/Mistral-7B-Instruct-v0.1`, etc.
- ✅︎
* - :code:`MixtralForCausalLM`
- Mixtral-8x7B, Mixtral-8x7B-Instruct
- :code:`mistralai/Mixtral-8x7B-v0.1`, :code:`mistralai/Mixtral-8x7B-Instruct-v0.1`, etc.
- ✅︎
* - :code:`MPTForCausalLM`
- MPT, MPT-Instruct, MPT-Chat, MPT-StoryWriter
- :code:`mosaicml/mpt-7b`, :code:`mosaicml/mpt-7b-storywriter`, :code:`mosaicml/mpt-30b`, etc.
-
* - :code:`OLMoForCausalLM`
- OLMo
- :code:`allenai/OLMo-1B`, :code:`allenai/OLMo-7B`, etc.
-
* - :code:`OPTForCausalLM`
- OPT, OPT-IML
- :code:`facebook/opt-66b`, :code:`facebook/opt-iml-max-30b`, etc.
-
* - :code:`OrionForCausalLM`
- Orion
- :code:`OrionStarAI/Orion-14B-Base`, :code:`OrionStarAI/Orion-14B-Chat`, etc.
-
* - :code:`PhiForCausalLM`
- Phi
- :code:`microsoft/phi-1_5`, :code:`microsoft/phi-2`, etc.
-
* - :code:`QWenLMHeadModel`
- Qwen
- :code:`Qwen/Qwen-7B`, :code:`Qwen/Qwen-7B-Chat`, etc.
-
* - :code:`Qwen2ForCausalLM`
- Qwen2
- :code:`Qwen/Qwen2-beta-7B`, :code:`Qwen/Qwen2-beta-7B-Chat`, etc.
- ✅︎
* - :code:`StableLmForCausalLM`
- StableLM
- :code:`stabilityai/stablelm-3b-4e1t/` , :code:`stabilityai/stablelm-base-alpha-7b-v2`, 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.
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