From 7d59b818d06ae65a317e450966c707def565fbed Mon Sep 17 00:00:00 2001 From: hsliuustc0106 Date: Fri, 10 Jul 2026 00:27:27 +0800 Subject: [PATCH] Remove LingBot-specific attention env Signed-off-by: hsliuustc0106 --- recipes/Robbyant/LingBot-Video.md | 4 ++-- .../models/lingbot_video/pipeline_lingbot_video.py | 6 ------ 2 files changed, 2 insertions(+), 8 deletions(-) diff --git a/recipes/Robbyant/LingBot-Video.md b/recipes/Robbyant/LingBot-Video.md index 8327af0e2..80a863c8f 100644 --- a/recipes/Robbyant/LingBot-Video.md +++ b/recipes/Robbyant/LingBot-Video.md @@ -45,7 +45,7 @@ resolution/frame count if your target workload runs out of memory. #### Offline T2V ```bash -CUDA_VISIBLE_DEVICES=0 LINGBOT_QWEN_ATTN_IMPLEMENTATION=sdpa \ +CUDA_VISIBLE_DEVICES=0 \ python examples/offline_inference/text_to_video/text_to_video_lingbot.py \ --model robbyant/lingbot-video-dense-1.3b \ --prompt "a robotic arm picks up a red block" \ @@ -63,7 +63,7 @@ python examples/offline_inference/text_to_video/text_to_video_lingbot.py \ #### Online Serving ```bash -CUDA_VISIBLE_DEVICES=0 LINGBOT_QWEN_ATTN_IMPLEMENTATION=sdpa \ +CUDA_VISIBLE_DEVICES=0 \ vllm serve robbyant/lingbot-video-dense-1.3b \ --omni \ --model-class-name LingBotVideoPipeline \ diff --git a/vllm_omni/diffusion/models/lingbot_video/pipeline_lingbot_video.py b/vllm_omni/diffusion/models/lingbot_video/pipeline_lingbot_video.py index ace4c0fe8..7f266069b 100644 --- a/vllm_omni/diffusion/models/lingbot_video/pipeline_lingbot_video.py +++ b/vllm_omni/diffusion/models/lingbot_video/pipeline_lingbot_video.py @@ -269,16 +269,10 @@ class LingBotVideoPipeline(nn.Module, ProgressBarMixin, SupportsComponentDiscove torch_dtype=transformer_dtype, local_files_only=local_files_only, ).to(self.device) - attn_implementation = os.environ.get( - "LINGBOT_QWEN_ATTN_IMPLEMENTATION", - str(model_config.get("qwen_attn_implementation", "sdpa")), - ) text_encoder_kwargs: dict[str, Any] = { "dtype": text_encoder_dtype, "local_files_only": local_files_only, } - if attn_implementation: - text_encoder_kwargs["attn_implementation"] = attn_implementation self.text_encoder = Qwen3VLForConditionalGeneration.from_pretrained( model, subfolder=text_encoder_subfolder,