Frank
689228e60d
Second half of the purge (the first covered the persona, AGENTS.md, README.md, and the distillation of the per-host pages). Every remaining identifier is gone: hostname, both LAN addresses, and the Wi-Fi SSID. 34 count-checked substitutions across 22 files — indexes, tool/research pages, the inventory census, the changelog, one generated HTML report, and five managed skills. Facts kept, names dropped: a history entry keeps its four-page listing as a nameless summary, the syslog excerpts keep every timestamp and line, and the census keeps the .zcompdump rows (the zsh version stamps are the useful part, the hostname was not). Deliberately unchanged: install.sh's --host case list and the packages/<hostname>.pkgs filename, where the hostname is the lookup key. Left out of scope by Frank's call: agent/memories/** — past-session records the learn pipeline rewrites. kb-lint: 0 violations. Residual grep for the hostname, its two IPs, and the SSID across omp-docs/ and agent/managed-skills/: no hits.
1.3 KiB
1.3 KiB
Ornith llama.cpp Setup
Complete reference for running Ornith-9B/35B MoE models with llama.cpp server on the workstation.
Concept Files
| File | Type | Description |
|---|---|---|
| api-endpoints.md | reference | Complete reference for health check, model listing, chat completions, and nat... |
| gpu-offloading.md | reference | How many GPU layers to offload based on your VRAM size for both Ornith 9B and... |
| installation.md | howto | Step-by-step setup — clone and build llama.cpp, download models, start the se... |
| model-specs.md | reference | Specifications for Ornith-1.0-9B dense and Ornith-1.0-35B MoE models — contex... |
| performance.md | reference | Token throughput benchmarks for Ornith 9B and 35B models with GPU vs CPU infe... |
| pi-configuration.md | howto | How to add Ornith models to models.json so pi can use the local llama.cpp ser... |
| systemd-service.md | howto | Set up llama.cpp server as a background service with systemd for persistent o... |
| troubleshooting.md | howto | Common errors — CUDA OOM, segfaults, model not responding, poor performance —... |