Evaluates Large Language Models across 100+ benchmarks using a reproducible, containerized framework.
The NeMo Evaluator SDK skill provides a comprehensive framework for benchmarking LLMs at scale, supporting over 100 standardized tests from 18+ evaluation harnesses like lm-evaluation-harness and HumanEval. It streamlines the evaluation process by offering containerized execution to ensure reproducibility across local Docker environments, Slurm HPC clusters, and cloud backends. This tool is ideal for developers and researchers who need to validate model performance, compare different architectures, and automate regression testing for mathematics, coding, and general instruction-following capabilities.
主な機能
01Unified interface for 18+ evaluation harnesses (simple-evals, bigcode, etc.)
02Multi-target support for NVIDIA NIM, vLLM, and OpenAI-compatible APIs
03Access to 100+ industry-standard benchmarks including MMLU, GSM8K, and HumanEval
04Containerized, reproducible execution across local, Slurm, and Lepton backends
050 GitHub stars
06Direct result exporting to MLflow, Weights & Biases, and local YAML formats
ユースケース
01Scaling massive evaluation pipelines across enterprise Slurm GPU clusters
02Comparing performance delta between different quantization levels and backends
03Benchmarking custom fine-tuned models against industry leaderboards
