[feat] Extend disaggregated MiniMax-H3 stage with VAE encoders (#6939)

Signed-off-by: asukaqaq-s <1311722138@qq.com>
Signed-off-by: Jader <yjader@foxmail.com>
Co-authored-by: Jader <yjader@foxmail.com>
Co-authored-by: Hongsheng Liu <liuhongsheng4@huawei.com>
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authored and GitHub committed 2026-09-16 16:52:35 +08:00
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@@ -23,6 +23,12 @@ One vLLM-Omni diffusion stage can load both DiTs while instantiating the
tokenizer, processor, Qwen3-VL text encoder, video VAE, and audio VAE only
once. Requests select the DiT with `extra_params.task`.
This single-stage recipe uses the default `model_loaded.text_encoder: true` and
`model_loaded.vae_encoder: true`. Precomputed text conditioning can replace the
local Qwen call. Setting `model_loaded.text_encoder: false` while leaving
`model_loaded.vae_encoder: true` requires precomputed text conditioning;
reference media is still encoded locally.
The generated MP4 contains H.264 video and synchronized stereo audio.
## Prerequisites
@@ -35,7 +41,7 @@ hf auth login
export MODEL=MiniMaxAI/MiniMax-H3
```
The vLLM-Omni pipeline downloads `FL2VA/**`, `Ref2VA/model_index.json`, and
By default, the pipeline downloads `FL2VA/**`, `Ref2VA/model_index.json`, and
`Ref2VA/transformer/**`. It does not download or load the diffusers-format
`transformer`, `transformer_ref`, or `vae` weights at the repository root, nor
duplicate Ref2VA copies of shared components.