nemo-evaluator-sdklisted
Install: claude install-skill qepilot/qepilot-stack
# NeMo Evaluator SDK - Enterprise LLM Benchmarking
## Quick Start
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**:
```bash
pip install nemo-evaluator-launcher
```
**Set API key and run evaluation**:
```bash
export NGC_API_KEY=nvapi-your-key-here
# Create minimal config
cat > config.yaml << 'EOF'
defaults:
- execution: local
- deployment: none
- _self_
execution:
output_dir: ./results
target:
api_endpoint:
model_id: meta/llama-3.1-8b-instruct
url: https://integrate.api.nvidia.com/v1/chat/completions
api_key_name: NGC_API_KEY
evaluation:
tasks:
- name: ifeval
EOF
# Run evaluation
nemo-evaluator-launcher run --config-dir . --config-name config
```
**View available tasks**:
```bash
nemo-evaluator-launcher ls tasks
```
## Common Workflows
### Workflow 1: Evaluate Model on Standard Benchmarks
Run core academic benchmarks (MMLU, GSM8K, IFEval) on any OpenAI-compatible endpoint.
**Checklist**:
```
Standard Evaluation:
- [ ] Step 1: Configure API endpoint
- [ ] Step 2: Select benchmarks
- [ ] Step 3: Run evaluation
- [ ] Step 4: Check results
```
**Step 1: Configure API endpoint**
```yaml
# config.yaml
defaults:
- execution: local
- deployment: none
- _self_
execution:
output_dir: ./results
target:
api_endpoint:
model_id: meta/llama-3.1-8b-instruct
url: https://int