NeMo Evaluator SDK
Skill Verifiziert AktivEvaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution. Use when needing scalable evaluation on local Docker, Slurm HPC, or cloud platforms. NVIDIA's enterprise-grade platform with container-first architecture for reproducible benchmarking.
To provide a scalable and reproducible platform for evaluating LLMs against a wide range of benchmarks, supporting enterprise needs for benchmarking on various computing infrastructures.
Funktionen
- Evaluate LLMs across 100+ benchmarks
- Supports 18+ evaluation harnesses (MMLU, HumanEval, VLM, safety)
- Multi-backend execution (Docker, Slurm, Cloud)
- Reproducible containerized evaluation
- Enterprise-grade platform with result export (MLflow, W&B)
Anwendungsfälle
- Running scalable LLM evaluations on local Docker instances
- Benchmarking LLMs on Slurm HPC clusters
- Comparing multiple models on standard academic and industry benchmarks
- Ensuring reproducible LLM evaluations through containerization
Nicht-Ziele
- Training or fine-tuning LLMs
- Providing raw model APIs
- General-purpose code generation or analysis beyond benchmark tasks
Workflow
- Configure evaluation parameters (execution backend, model endpoint, tasks)
- Select benchmarks and optionally override parameters per task
- Launch evaluation via CLI or Python API
- Monitor job status and retrieve results
- Export results for comparison and analysis
Praktiken
- Benchmarking
- LLM Evaluation
- Reproducible Computing
- Distributed Systems
Voraussetzungen
- Docker installed and running (for local execution)
- SSH access to Slurm cluster (for Slurm execution)
- NGC API Key (for container pulls and NVIDIA services)
- HF_TOKEN (for some benchmarks)
Installation
npx skills add davila7/claude-code-templatesFührt das Vercel skills CLI (skills.sh) via npx aus — benötigt Node.js lokal und mindestens einen installierten skills-kompatiblen Agent (Claude Code, Cursor, Codex, …). Setzt voraus, dass das Repo dem agentskills.io-Format folgt.
Qualitätspunktzahl
VerifiziertVertrauenssignale
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