Data Science & Analytics
Modelopt Compare Results
Establish baseline-vs-candidate evaluation plans, delegate missing evaluations, compare validated results, and decide quantization feasibility. Use when the user asks to compare baseline vs quantized runs, explain an accuracy drop/regression, verify whether a quantized checkpoint is acceptable, or compare NEL/MLflow evaluation outputs. Do NOT use for generic single-model evaluation without comparison intent (use modelopt-evaluation), live NEL status/debugging (use modelopt-launching-evals), or generic MLflow browsing without a comparison goal (use modelopt-accessing-mlflow).
- Publisher / source
- NVIDIA/Model-Optimizer (found on GitHub top repositories)
- Upstream record
- NVIDIA/Model-Optimizer
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
abc4971354c53984af2958c8aaca765d28531f83199e6ce5ce0a71a61b99e9d7