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Cross-check SharpInference numerics against llama.cpp and run accuracy gates. Use when output quality or numerics are in question — new architecture bring-up, kernel or quantization changes, KV-compression work, "model produces garbage" reports.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Drive the architect→workhorse flow — turn an approved plan into delegated Sonnet implementation with test and review gates, keeping the main (Opus/Fable) thread as coordinator.
Work a GitHub issue end-to-end — fetch it, verify the claim, turn it into an architect spec, and drive the delegated implementation flow with correct issue references in branches and commits.
Checklist for adding support for a new GGUF model architecture (or a variant of an existing one) to SharpInference.
CLI run recipes for specific models and modes — VibeThinker, Ornith-1.0, Gemma 4 vision, image generation + upscaling, perplexity gating, whole-turn JSON-schema structured output, DSpark speculative decoding, download-model presets. Use when actually running inference for one of these.
Required workflow when adding, editing, or removing Vulkan GLSL shader consts — the committed precompiled SPIR-V table must be regenerated or tests fail on drift.
| name | parity-check |
| description | Cross-check SharpInference numerics against llama.cpp and run accuracy gates. Use when output quality or numerics are in question — new architecture bring-up, kernel or quantization changes, KV-compression work, "model produces garbage" reports. |
Escalate through these levels; stop at the first one that answers the question.
tests/SharpInference.Tests.ForwardPass holds quantization and kernel parity
suites (CPU vs CUDA vs Vulkan, Q4_K/Q6_K/Q8 dequant round-trips). Run the
narrowest filter first — this catches most kernel regressions without any GGUF.
pwsh scripts/xcheck-llamacpp.ps1 -Model <gguf> -Prompt "..." -NTokens 30 -Tag <tag>
tools/llama.cpp (fetch via pwsh scripts/setup-llamacpp.ps1) and a
Release build of the CLI (dotnet build src/SharpInference.Cli -c Release).--temp 0 and prints SharpInference's greedy token IDs;
outputs land in tools/xcheck_<tag>_*.txt for diffing.pwsh scripts/generate-reference-logits.ps1 plus scripts/extract_reference.py /
scripts/compare_tokens.py produce and compare per-position logits when token-level
divergence needs a numeric root cause.
dotnet run --project src/SharpInference.Cli -c Release -- \
perplexity -m <model.gguf> -f <corpus.txt> -c 2048 [--tq] [--tq-mode kvarn|lloydmax]
The accuracy gate for KV compression and lossy changes (issue #180). Compare
against a baseline run without the change; corpus helpers live in
scripts/kvarn-gate/ (get-wikitext2.ps1, math-eval.ps1).
models/; fetch known presets with
pwsh scripts/download-model.ps1 -Model <preset> (see script header for the list).