Nemo Evaluator Sdk
ListedThe Nemo Evaluator SDK allows developers to rapidly assess and compare model performance across diverse datasets, streamlining AI development workflows.
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Showing Claude Code. One command installs this skill into any of the agents below.
- 1
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terminal$ npx skills add orchestra-research/ai-research-skills --skill nemo-evaluator-sdk -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
orchestra-research
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Live repository
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Automated safety checks
This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.
No credential access: failed
Touches credential material in 2 places.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
What it found
- 11-evaluation/nemo-evaluator/references/execution-backends.md:113SSH private keys or config
ssh_key_path: ~/.ssh/id_rsa - 11-evaluation/nemo-evaluator/references/execution-backends.md:336SSH private keys or config
chmod 600 ~/.ssh/id_rsa
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned orchestra-research/ai-research-skills at 773a52944b.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 773a52944b
- Scanned
- 5 files, 1,762 lines
About this skill
What it does
The orchestra-research-nemo-evaluator-sdk skill provides tools for evaluating and analyzing AI models, specifically within the NVIDIA Nemo framework. It allows users to run evaluation pipelines, generate reports on model performance, and compare different model configurations. This SDK streamlines the process of assessing and improving AI model quality.
When to use it
- Model Performance Benchmarking: Compare the accuracy and efficiency of different language models for a specific task.
- Regression Testing: Ensure that changes to an existing model don't negatively impact its performance on established benchmarks.
- Automated Evaluation Pipelines: Integrate evaluation steps into your AI development workflow, automatically generating reports after each training run.
- Research and Development: Experiment with new model architectures or training techniques and quickly assess their effectiveness.
Key capabilities
- Nemo framework integration
- Evaluation pipeline execution
- Performance report generation
- Model comparison functionality
Example prompts
- "Run the standard evaluation pipeline for this language model."
- "Generate a performance report comparing Model A and Model B on the speech recognition task."
- "Evaluate this new model against the baseline configuration."
Tips & gotchas
This skill requires familiarity with the NVIDIA Nemo framework. Ensure that you have the necessary dependencies installed before attempting to use it.