Use when the user requests integration testing, feature validation, or test plan execution
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av/skills202026年10月12日 更新
免费在 GitHub 公开
pull-llamacpp-model
Use when pulling or downloading a new llamacpp model. The active ROCm image (kyuz0/amd-strix-halo-toolboxes) fails to start in the ephemeral pull container without ROCm device access. Must temporarily switch to the standard CPU image.
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查看安装方法包含的文件（2）
- SKILL.md1.6 KB
- README.md559 B
SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
Pull a llamacpp Model
This machine uses kyuz0/amd-strix-halo-toolboxes:rocm-7.2 for llamacpp inference (AMD Strix Halo / gfx1151 — not supported by the official ROCm build). Harbor's pull mechanism starts an ephemeral container with --n-gpu-layers 0; the custom image fails in that context without ROCm device access. Use the standard CPU image just for pulling, then restore.
Steps
1. Switch to the standard CPU image
harbor config set llamacpp.image.rocm ghcr.io/ggml-org/llama.cpp:server
2. Pull the model
harbor pull <hf-owner/model-repo:quantization>
# Examples:
harbor pull bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M
harbor pull unsloth/Mistral-Small-3.1-24B-Instruct-2503-GGUF:UD-Q4_K_XL
Harbor detects the HuggingFace model spec and routes it through llamacpp automatically.
3. Restore the custom image
harbor config set llamacpp.image.rocm kyuz0/amd-strix-halo-toolboxes:rocm-7.2
Notes
- The restore step is mandatory — without it, llamacpp will not use the GPU on the next
harbor up llamacpp - Extra args (
-fa 1 -dio --no-mmap --ctx-size 64000 --fit off) are stored separately in config and are not affected - To verify the model after pulling:
harbor llamacpp model - To verify the image was restored:
harbor config get llamacpp.image.rocm
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