biondizzle
f5ce728ef2
The CPU dummy weight broke torch.mm(compressor.weight.T) which expects GPU tensors. Instead, reduce max_model_len to fit KV cache within available memory (876544 instead of 1048576).
38 lines
989 B
YAML
38 lines
989 B
YAML
services:
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vllm:
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build:
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context: .
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dockerfile: Dockerfile
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ports:
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- "8000:8000"
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environment:
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- OMP_NUM_THREADS=128
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- CUDA_LAUNCH_BLOCKING=0
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- PYTHONUNBUFFERED=1
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- VLLM_RPC_TIMEOUT_MS=600000
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- CLAWMINE_DEBUG=1
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command:
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- /model
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- --trust-remote-code
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- --enable-expert-parallel
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- --tensor-parallel-size=8
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- --compilation-config={"cudagraph_mode":"NONE","custom_ops":["all"]}
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- --tokenizer-mode=deepseek_v4
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- --tool-call-parser=deepseek_v4
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- --enable-auto-tool-choice
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- --reasoning-parser=deepseek_v4
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- --moe-backend=cutedsl
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- --gpu-memory-utilization=0.9
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- --max-model-len=876544
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- --host=0.0.0.0
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- --port=8000
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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volumes:
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- /root/nvidia-meeting/DeepSeek-V4-Pro-NVFP4:/model:ro
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