310491a557
- Updated python_coding_microproject.csv to use NVIDIA NIM Kimi K2 - Updated kali_linux_shell_simulator.csv to use NVIDIA NIM Kimi K2 - Made more general-purpose (flexible targets, expanded tools) - Added nemotron-mini-agent.csv for fast local inference via Ollama - Added nemotron-agent.csv for advanced reasoning via Ollama - Added wiki page: Projects for NVIDIA NIMs and Nemotron
25 lines
709 B
YAML
25 lines
709 B
YAML
# Docker Compose x86_64 GPU Overlay
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# Auto-applied by installer when NVIDIA GPU + Container Toolkit detected
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# This overlay enables GPU passthrough for the vLLM embeddings container
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services:
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vllm-embeddings:
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deploy:
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resources:
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# GPU mode: model loads into VRAM (~2.5GB), minimal system RAM needed
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limits:
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memory: 4G
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reservations:
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memory: 2G
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devices:
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- driver: nvidia
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count: 1
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capabilities: [gpu]
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environment:
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# GPU-specific settings
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- CUDA_VISIBLE_DEVICES=0
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- PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
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labels:
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- "gt2.gpu=enabled"
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- "gt2.gpu.vendor=nvidia"
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