evaluation-nemo-evaluator

原文涵盖的主题

• NeMo Evaluator SDK - Enterprise LLM Benchmarking
• Quick Start
• Common Workflows
• Workflow 1: Evaluate Model on Standard Benchmarks
• Workflow 2: Run Evaluation on Slurm HPC Cluster
• Workflow 3: Compare Multiple Models
• Workflow 4: Safety and Vision-Language Evaluation
• When to Use vs Alternatives

NeMo Evaluator SDK evaluates LLMs across 100+ benchmarks from 18+ harnesses using containerized, reproducible evaluation with multi-backend execution (local Docker, Slurm HPC, Lepton cloud). Installation: Set API key and run evaluation: View available tasks: Run core academic benchmarks (MMLU, GSM8K, IFEval) on any OpenAI-compatible endpoint. Checklist: Step 1: Configure API endpoint For self-hosted endpoints (vLLM, TRT-LLM): Step 2: Select benchmarks Add tasks to your config: Step 3: Run evaluation Step 4: Check results Execute large-scale evaluation on HPC infrastructure. Checklist: Step 1: Configure Slurm settings Step 2: Set up model deployment Step 3: Launch evaluation Step 4: Monitor job status Benchmark multiple models on the same tasks for comparison. Checklist: Step 1: Create base config Step 2: Run evaluations with model overrides Step 3: Export and compare Evaluate models on safety benchmarks and VLM tasks. Checklist: Step 1: Configure safety tasks Step 2: Configure VLM tasks Use NeMo Evaluator when: Need 100+ benchmarks from 18+ harnesses in one platform Running evaluations on Slurm HPC clusters or cloud Requiring reproducible containerized evaluation Evaluating against

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