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[Doc] Update Qwen documentation #9869

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Oct 31, 2024
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9 changes: 5 additions & 4 deletions docs/source/models/supported_models.rst
Original file line number Diff line number Diff line change
Expand Up @@ -277,7 +277,7 @@ Text Generation
* - :code:`QWenLMHeadModel`
- Qwen
- :code:`Qwen/Qwen-7B`, :code:`Qwen/Qwen-7B-Chat`, etc.
-
- ✅︎
- ✅︎
* - :code:`Qwen2ForCausalLM`
- Qwen2
Expand Down Expand Up @@ -414,7 +414,7 @@ Text Generation
- Models
- Inputs
- Example HF Models
- :ref:`LoRA <lora>`
- :ref:`LoRA (see note) <lora>`
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- :ref:`PP <distributed_serving>`
* - :code:`Blip2ForConditionalGeneration`
- BLIP-2
Expand Down Expand Up @@ -516,7 +516,7 @@ Text Generation
- Qwen-VL
- T + I\ :sup:`E+`
- :code:`Qwen/Qwen-VL`, :code:`Qwen/Qwen-VL-Chat`, etc.
-
- ✅︎
- ✅︎
* - :code:`Qwen2AudioForConditionalGeneration`
- Qwen2-Audio
Expand All @@ -541,8 +541,9 @@ Text Generation
| :sup:`+` Multiple items can be inputted per text prompt for this modality.

.. note::
For :code:`openbmb/MiniCPM-V-2`, the official repo doesn't work yet, so we need to use a fork (:code:`HwwwH/MiniCPM-V-2`) for now.
- For :code:`openbmb/MiniCPM-V-2`, the official repo doesn't work yet, so we need to use a fork (:code:`HwwwH/MiniCPM-V-2`) for now.
For more details, please see: https://github.com/vllm-project/vllm/pull/4087#issuecomment-2250397630
- Regarding multimodal models, vLLM currently only supports adding LoRA to language model.
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Multimodal Embedding
--------------------
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2 changes: 1 addition & 1 deletion vllm/model_executor/models/qwen.py
Original file line number Diff line number Diff line change
Expand Up @@ -1048,7 +1048,7 @@ def get_mm_mapping(self) -> MultiModelKeys:
@MULTIMODAL_REGISTRY.register_max_image_tokens(MAX_QWEN_IMG_TOKENS)
@INPUT_REGISTRY.register_dummy_data(dummy_data_for_qwen)
@INPUT_REGISTRY.register_input_processor(input_processor_for_qwen)
class QWenLMHeadModel(QWenBaseModel):
class QWenLMHeadModel(QWenBaseModel, SupportsLoRA):
"""
QWenLMHeadModel is not only applicable to LLM but also to VL, which is not
conducive to the current integration logic of LoRA in vLLM. Therefore, it
Expand Down