Frank
d9af7f1d19
- Move all previous scripts to old/scripts/ (retired PP/NPU-era) - frank-default-large: llama.cpp FastMTP on dankserver (HauhauCS Qwen3.8-27B IQ4_XS + FastMTP 32K draft + ngram-mod, K q8_0/V f16, 128K ctx, batch 2048/ubatch 1024, port 7770) - frank-default-small: vLLM ROCm on dankclaw (Avesed Qwen3.6-35B-A3B INT8 W8A8, full 262144 ctx, no KV quant, 4 seqs, batch 16384, ngram spec, port 52625) - retarget deploy.sh (dankserver/dankclaw, inline sudo, no helpers) - docs: deployment + index + AGENTS.md + README for new topology, superseded banners on retired docs, add frank-redo-2026-08-17 runbook
57 lines
2.0 KiB
Bash
Executable File
57 lines
2.0 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Serve Qwen3.6-35B-A3B-FP8 with DFlash speculative decoding via vLLM on NVIDIA RTX 3090
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# Uses Podman container with CUDA support
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# 4 parallel streams, full context (262K) each
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set -euo pipefail
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# Configuration
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MODEL="${MODEL:-Qwen/Qwen3.6-35B-A3B-FP8}"
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DRAFT_MODEL="${DRAFT_MODEL:-z-lab/Qwen3.6-35B-A3B-DFlash}"
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PORT="${PORT:-8000}"
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GPU_MEM_UTIL="${GPU_MEM_UTIL:-0.95}"
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MAX_NUM_SEQS="${MAX_NUM_SEQS:-4}"
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MAX_MODEL_LEN="${MAX_MODEL_LEN:-262144}"
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KV_CACHE_DTYPE="${KV_CACHE_DTYPE:-fp8}"
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NUM_SPEC_TOKENS="${NUM_SPEC_TOKENS:-8}"
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CONTAINER_NAME="${CONTAINER_NAME:-vllm-qwen36-dflash}"
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HF_CACHE="${HF_CACHE:-/home/dank/.cache/huggingface}"
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GPU_LIBS="${GPU_LIBS:-/usr/lib/x86_64-linux-gnu}"
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echo "Starting vLLM server in Podman..."
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echo " Target model: ${MODEL}"
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echo " Draft model: ${DRAFT_MODEL}"
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echo " Port: ${PORT}"
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echo " GPU mem util: ${GPU_MEM_UTIL}"
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echo " Max seqs: ${MAX_NUM_SEQS}"
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echo " Context len: ${MAX_MODEL_LEN}"
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echo " KV cache: ${KV_CACHE_DTYPE}"
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echo " Spec tokens: ${NUM_SPEC_TOKENS}"
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echo ""
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# Remove existing container if present
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podman rm -f "${CONTAINER_NAME}" 2>/dev/null || true
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# Run vLLM in Podman container (foreground mode for systemd)
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# Note: vllm/vllm-openai image has entrypoint "vllm serve", so we pass args directly
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exec podman run --name "${CONTAINER_NAME}" \
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--device /dev/nvidia0 \
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--device /dev/nvidiactl \
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--device /dev/nvidia-uvm \
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--device /dev/nvidia-uvm-tools \
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--device /dev/nvidia-modeset \
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-v "${GPU_LIBS}:/usr/lib/x86_64-linux-gnu:ro" \
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-v "${HF_CACHE}:/root/.cache/huggingface" \
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-p "${PORT}:${PORT}" \
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docker.io/vllm/vllm-openai:latest \
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"${MODEL}" \
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--port "${PORT}" \
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--host "0.0.0.0" \
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--kv-cache-dtype "${KV_CACHE_DTYPE}" \
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--gpu-memory-utilization "${GPU_MEM_UTIL}" \
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--max-num-seqs "${MAX_NUM_SEQS}" \
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--max-model-len "${MAX_MODEL_LEN}" \
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--spec-method dflash \
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--spec-model "${DRAFT_MODEL}" \
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--spec-tokens "${NUM_SPEC_TOKENS}" \
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--trust-remote-code
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