writing-skills
writing-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment
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배포 및 운영 · SKILL.md
lora_merge_latency
lora_merge_latencyMerge LoRA low-rank factors into a dense weight and verify deployment-equivalent inference.
Independent GitHub snapshot · Automated classification · Original documentation governs
Skill 문서
GitHubname: lora_merge_latency description: Merge LoRA low-rank factors into a dense weight and verify deployment-equivalent inference.
LoRA Merge Latency
Use this skill when deploying or validating LoRA without extra inference latency. It consumes a base weight and trained factors and emits a merged dense matrix plus equivalence checks.
Inputs
W0, A, B, alpha, and test inputs.
Outputs
Merged weight W, unmerged-vs-merged maximum error, and optional restored base weight.
Workflow
Compute W = W0 + (alpha/r) BA, run the ordinary dense layer, compare it with the unmerged LoRA forward pass, and record a tight numerical tolerance.
Validation
Run the included tests or validate the skill tree with tests.
Limitations
Merging one adapter at a time is appropriate for single-task batches; mixed adapters may require unmerged dynamic routing.