588-line vllm model implementation based on qwen3_moe.py.
Bootstrap strategy: treat ALL layers as full attention (ignoring
linear_attention optimization). Correct but suboptimal.
Key adaptations:
- _get_text_config(): unwrap composite config -> text_config
- Shared expert support (shared_expert_intermediate_size)
- Skip linear attention weights (conv1d, delta_net, gated_delta)
- Skip vision encoder and MTP weights
- QK norm (Qwen3 style)
- Partial rotary embedding (rope_pct=0.25)
Includes deploy.sh and run_baseline.sh for server deployment.