rnnt

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MLPerf inference benchmark

Speech recognition with RNNT

Notes

In the edge category, ResNet50 has Offline, SingleStream and MultiStream scenarios and in the datacenter category, it has Offline and Server scenarios.

Please check MLPerf inference GitHub for more details.

Run using the MLCommons CM framework

From Feb 2024, we suggest you to use this GUI to configure MLPerf inference benchmark, generate CM commands to run it across different implementations, models, data sets, software and hardware, and prepare your submissions.

A few ready-to-use CM commands

Install MLCommons CM automation framework with automation recipes for MLPerf as described here.

The following guides explain how to run different implementations of this benchmark via CM:

• MLCommons Reference implementation in Python
• NVIDIA optimized implementation (GPU)

Questions? Suggestions?

Check the MLCommons Task Force on Automation and Reproducibility and get in touch via public Discord server.