IEEE P3193

New IEEE Standard - Active - Draft.
This recommended practice provides a framework for the use of large-scale pre-trained deep learning models, including approaches, taxonomies, related roles, and activities, software toolkits, application ability key performance indicators as well as assessment means.

This document provides a framework for the use of large-scale pre-trained deep learning models (LPDLMs), covering the following areas:
1) Approaches for using LPDLMs as well as the related roles, taxonomies, and activities. On top of this, an application provider is enabled to check and optimize the organizational settings for quality enhancement;
2) Recommended practice on software toolkits for using models, which helps application providers to improve their efficiency when satisfying industrial requirements;
3) A set of assessment means for industrial application providers to systematically identify issues in their processes during using LPDLMs.
This document and IEEE P3142 complement each other. LPDLM-related training and inference approaches and the key performance indicators of LPDLMs are covered by IEEE P3142, while this document focuses on the use of LPDLMs.