trace-model

Validate per-layer AI model inference outputs against traces.safetensors.

1.7k|68|Updated Jun 23, 2025
One-click install
npx skills add https://github.com/trymirai/uzu --skill trace-model
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: trace-model
Source: https://github.com/trymirai/uzu/tree/main/agents/skills/trace-model
Command: npx skills add https://github.com/trymirai/uzu --skill trace-model

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Validate intermediate calculations during AI model inference against a source of truth traces to ensure numerical correctness across layers.

Core Features & Use Cases

  • Compare per-layer outputs to traces.safetensors to detect drift
  • Integrate with existing CI/tests to catch regressions in model inference
  • Provide traceability by storing layer-wise results for audits

Quick Start

Run the tracer test to verify model layer outputs against the source-of-truth traces.

Frequently Asked Questions about trace-model

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate intermediate calculations during AI model inference?▼

Validate intermediate calculations by running a tracer test that compares per-layer outputs against source-of-truth traces stored in traces.safetensors to detect numerical drift across layers.

How do I detect numerical drift in model inference layers?▼

Detect numerical drift by comparing per-layer outputs against source-of-truth traces stored in traces.safetensors to ensure numerical correctness across layers.

How do I integrate trace validation into my project test suite?▼

Integrate trace validation by running the tracer test within your project test suite, requiring access to traces.safetensors stored alongside the model to compare per-layer results after each inference stage.

Do I need traces.safetensors available to validate intermediate inference calculations?▼

Yes, you need traces.safetensors stored alongside the model to validate intermediate inference calculations and compare per-layer results after each inference stage.

How do I catch regressions in model inference within CI pipelines?▼

Catch regressions in model inference within CI pipelines by integrating the tracer test to compare layer-wise results against traces.safetensors, providing traceability for audits.

What is the best way to ensure numerical correctness across AI model layers?▼

Ensure numerical correctness across AI model layers by validating intermediate calculations against source-of-truth traces using traces.safetensors to detect drift after each inference stage.