47 lines
1.2 KiB
YAML
47 lines
1.2 KiB
YAML
services:
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llama4:
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build:
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context: .
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dockerfile: Dockerfile
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image: llama4-bi150:${TAG:-2026-10-26}
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container_name: llama4
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# vLLM 多卡 NCCL / 端口直通
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network_mode: host
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ipc: host
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# Iluvatar 运行时要求
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privileged: true
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pid: host
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volumes:
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- /dev:/dev
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- ${MODEL_HOST_DIR:-/mnt/disk0/models/LLM-Research/Llama-4-Scout-17B-16E-Instruct}:/models/llama4:ro
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environment:
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MODEL_PATH: /models/llama4
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AUTO_DETECT: "1"
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HOST: 0.0.0.0
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# 默认暴露全部 16 张卡；entrypoint 会根据模型选择实际 TP*PP。
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CUDA_VISIBLE_DEVICES: "${GPUS:-0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15}"
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# 留空时由 entrypoint 根据 config.json 自动判断。
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# 如果需要手动覆盖，取消注释并填值。
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# TP: "${TP:-}"
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# PP: "${PP:-}"
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# PORT: "${PORT:-}"
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# SERVED_NAME: "${SERVED_NAME:-}"
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MAX_MODEL_LEN: "${MAX_MODEL_LEN:-4096}"
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MAX_NUM_SEQS: "${MAX_NUM_SEQS:-1}"
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GPU_MEM_UTIL: "${GPU_MEM_UTIL:-0.90}"
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ENFORCE_EAGER: "${ENFORCE_EAGER:-1}"
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EXTRA_ARGS: "${EXTRA_ARGS:-}"
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ulimits:
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memlock: -1
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stack: 67108864
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restart: unless-stopped
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