Invention Grant
- Patent Title: Documentation file-embedded machine learning models
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Application No.: US18183120Application Date: 2023-03-13
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Publication No.: US12008448B2Publication Date: 2024-06-11
- Inventor: Changchuan Yin
- Applicant: AT&T Intellectual Property I, L.P.
- Applicant Address: US GA Atlanta
- Assignee: AT&T Intellect al P Property I, L.P.
- Current Assignee: AT&T Intellect al P Property I, L.P.
- Current Assignee Address: US GA Atlanta
- Main IPC: G06F40/103
- IPC: G06F40/103 ; G06N20/00

Abstract:
A processing system including at least one processor may obtain a machine learning model, serialize the machine learning model into a serialized format, and embed a delimiter indicator into a documentation file comprising information regarding the use of the machine learning model, where the delimiter indicator is in a file position that is after an end-of-file indicator of the documentation file. The processing system may further embed the machine learning model in the serialized format into the documentation file in a file position that is after the delimiter indicator. The processing system may then store the documentation file with the delimiter indicator and the machine learning model in the serialized format that are embedded.
Public/Granted literature
- US20230222389A1 DOCUMENTATION FILE-EMBEDDED MACHINE LEARNING MODELS Public/Granted day:2023-07-13
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