From 11b6c160078bca5a4d38e39d3383ce173b547d63 Mon Sep 17 00:00:00 2001 From: tzhouam Date: Wed, 11 Mar 2026 19:24:44 +0000 Subject: [PATCH] rebase: align vllm-omni with vLLM 84e436ed1c94 Signed-off-by: tzhouam --- .../model_executor/models/qwen3_omni/qwen3_omni_moe_thinker.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/vllm_omni/model_executor/models/qwen3_omni/qwen3_omni_moe_thinker.py b/vllm_omni/model_executor/models/qwen3_omni/qwen3_omni_moe_thinker.py index 852d5572b..a0baefca7 100644 --- a/vllm_omni/model_executor/models/qwen3_omni/qwen3_omni_moe_thinker.py +++ b/vllm_omni/model_executor/models/qwen3_omni/qwen3_omni_moe_thinker.py @@ -942,7 +942,7 @@ class Qwen3OmniMoeThinkerForConditionalGeneration( return [] # The result multimodal_embeddings is tuple of tensors, with each - # tensor correspoending to a multimodal data item (image or video). + # tensor corresponding to a multimodal data item (image or video). multimodal_embeddings: tuple[torch.Tensor, ...] = () # NOTE: It is important to iterate over the keys in this dictionary