59 lines
1.9 KiB
Bash
Executable File
59 lines
1.9 KiB
Bash
Executable File
#!/bin/bash
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# llama-server launcher for Qwen3.8-27B on Turing GPUs (RTX 2060 12GB + CMP 50HX 10GB)
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# Built with NVIDIA NCCL for hardware-accelerated multi-GPU tensor parallelism.
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# Accelerated with HauhauCS FastMTP 32K draft sidecar and official thinking parameters.
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export LD_LIBRARY_PATH=/opt/llama.cpp-xrip/build-nccl/bin:/opt/minicpm-venv/lib/python3.13/site-packages/nvidia/nccl/lib:/lib/x86_64-linux-gnu
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# Low-Latency NCCL & CUDA Driver Pipeline Optimizations
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export CUDA_DEVICE_MAX_CONNECTIONS=1
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export NCCL_BUFFSIZE=2097152
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export NCCL_NET_GDR_LEVEL=0
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export NCCL_P2P_DISABLE=0
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export NCCL_ALGO=RING
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export NCCL_PROTO=SIMPLE
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# Dynamically target the 12GB RTX 2060 for mmproj and FastMTP draft model
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RTX_DEV=$(/opt/llama.cpp-xrip/build-nccl/bin/llama-cli --list-devices | grep -i "RTX 2060" | awk '{print $1}' | tr -d ':')
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RTX_DEV=${RTX_DEV:-CUDA0}
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exec /opt/llama.cpp-xrip/build-nccl/bin/llama-server \
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-m /opt/models/gguf/Qwen3.8-27B-Uncensored-HauhauCS-Aggressive-Q5_K_P.gguf \
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--spec-draft-model /opt/models/gguf/Qwen3.8-27B-Uncensored-HauhauCS-Aggressive-FastMTP-32K.gguf \
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--spec-draft-device "$RTX_DEV" \
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--spec-draft-ngl all \
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--spec-type draft-mtp \
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--spec-draft-n-max 3 \
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--spec-draft-p-min 0 \
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--mmproj /opt/models/gguf/mmproj-Qwen3.8-27B-Uncensored-f16.gguf \
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--mmproj-device "$RTX_DEV" \
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--image-min-tokens 1024 \
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--temp 1.0 \
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--top-k 20 \
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--top-p 0.95 \
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--min-p 0 \
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--presence-penalty 0 \
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--repeat-penalty 1.0 \
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--reasoning on \
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--reasoning-effort xhigh \
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--reasoning-preserve \
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--reasoning-format deepseek \
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--numa isolate \
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-ngl 99 \
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-c 131072 \
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--parallel 1 \
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--cache-prompt \
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--cache-reuse 64 \
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--cache-idle-slots \
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--slot-prompt-similarity 0.10 \
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--cache-ram 32768 \
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--slot-save-path /var/cache/llama-slots \
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--split-mode tensor \
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--flash-attn on \
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--batch-size 2048 \
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--ubatch-size 1024 \
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--jinja \
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--threads 12 \
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--cache-type-k q5_0 \
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--cache-type-v q5_0 \
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--host 0.0.0.0 \
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--port 8080 |