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Linear layers (400 modules: attention, MLP and GatedDeltaNet projections) → compressed-tensors pack-quantized (served by vLLM's Marlin kernels).model.visual.*, 333 tensors)mtp.*, 15 tensors) — enables speculative decodinglm_head, embeddings, norms, conv1d, and the GatedDeltaNet in_proj_a/in_proj_b projections (output dim 48 < group_size 128)DoktorMincs/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-MTP-W4A16-AutoRound to load directly from the Hub:1export CUDA_DEVICE_ORDER=PCI_BUS_ID
2export OMP_NUM_THREADS=4
3export CUDA_VISIBLE_DEVICES=0,1,2,3
4export PYTORCH_ALLOC_CONF=expandable_segments:True
5export NCCL_P2P_DISABLE=1
6export FLASHINFER_DISABLE_VERSION_CHECK=1
7
8exec vllm serve \
9 /root/models/DoktorMincs/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-MTP-W4A16-AutoRound \
10 --served-model-name "qwen3.6-27b" \
11 --tensor-parallel-size 4 \
12 --max-model-len 163840 \
13 --override-generation-config '{"temperature": 0.6, "top_p": 0.95, "top_k": 20, "min_p": 0.0, "presence_penalty": 0.0, "repetition_penalty": 1.0}' \
14 --tool-call-parser qwen3_coder \
15 --reasoning-parser qwen3 \
16 --enable-auto-tool-choice \
17 --trust-remote-code \
18 --enable-prefix-caching \
19 --max-num-batched-tokens 8192 \
20 --gpu-memory-utilization 0.88 \
21 --disable-custom-all-reduce \
22 --max-num-seqs 16 \
23 --host 0.0.0.0 \
24 --port 3434 \
25 --speculative-config '{"method": "mtp", "num_speculative_tokens": 1}'Qwen3_5ForConditionalGeneration (hybrid: 64 layers, 3:1 GatedDeltaNet linear-attention : full-attention, 27-block ViT, 1 MTP layer).chat_template-instruct.jinja is the author's alternate template shipped with the base model.