[Misc] Consolidate LingBot text-to-video runner
Signed-off-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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@@ -12,6 +12,7 @@ For backend selection and SageAttention usage, see the [Diffusion Attention Back
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| Model | Default Resolution | Default Frames | Default Steps | Guidance | VRAM (BF16) |
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|---|---|---|---|---|---|
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| `Wan-AI/Wan2.2-T2V-A14B-Diffusers` | 720x1280 | 81 | 40 | 4.0 | ~60 GiB |
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| `robbyant/lingbot-video-dense-1.3b` / `robbyant/lingbot-video-moe-30b-a3b` | 192x320 | 9 | 2 | 3.0 | ~68 GiB (MoE smoke) |
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| `Lightricks/LTX-2` | 512x768 | 121 | 40 | video 3.0 / audio 7.0 | Model-dependent |
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| `hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-480p_t2v` | 480x832 | 121 | 50 | 6.0 | 1×A100 80GB |
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| `hunyuanvideo-community/HunyuanVideo-1.5-Diffusers-720p_t2v` | 720x1280 | 121 | 50 | 6.0 | FP8 + VAE tiling required |
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@@ -35,6 +36,25 @@ python text_to_video.py \
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--output t2v_out.mp4
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```
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### LingBot-Video
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The shared runner recognizes both official LingBot checkpoint IDs and selects
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the native `LingBotVideoPipeline` automatically:
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```bash
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python text_to_video.py \
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--model robbyant/lingbot-video-dense-1.3b \
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--prompt "a robotic arm picks up a red block" \
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--height 192 --width 320 --num-frames 9 --num-inference-steps 2 \
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--guidance-scale 3.0 --flow-shift 3.0 --fps 24 \
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--output lingbot_t2v.mp4
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```
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Use `robbyant/lingbot-video-moe-30b-a3b` for the MoE checkpoint. For local
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paths without `lingbot` in the directory name, add
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`--model-class-name LingBotVideoPipeline`. Model-only options use
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`--extra-body`, for example `'{"batch_cfg": true, "output_type": "np"}'`.
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### LTX-2
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```bash
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