Techniques for effectively eliminating input size limits of machine learning models
AssigneeApple Inc.
InventorsXiaohui TAO, James BYUN, Jason GE, Wentao WU, Yang ZHAO
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Abstract
The present disclosure generally relates to implementing machine learning models. More particularly, the described embodiments provide techniques for effectively eliminating input size limits of machine learning models. Some techniques are for processing text using machine learning (ML) models.
Claims30
A method, comprising, by a server computing device:
- receiving a query from a client computing device, wherein the query comprises a request to generate a summary of text content included in the query;
- determining that a size of the text content exceeds an input limit associated with an ML model to be utilized to generate the summary;
- separating the text content into a plurality of text segments, wherein each text segment of the plurality of text segments is sized in accordance with the input limit;
- for each text segment of the plurality of text segments:
- generating, using the ML model, a respective text summary based on the text segment, and
- adding the respective text summary to a plurality of text summaries;
- generating the summary based on the plurality of text summaries;
- and
- causing the summary to be output by way of a user interface on the client computing device.
A non-transitory computer readable storage medium configured to store instructions that, when executed by at least one processor included in a server computing device, cause the server computing device to carry out steps that include:
- receiving a query from a client computing device, wherein the query comprises a request to generate a summary of text content included in the query;
- determining that a size of the text content exceeds an input limit associated with an ML model to be utilized to generate the summary;
- separating the text content into a plurality of text segments, wherein each text segment of the plurality of text segments is sized in accordance with the input limit;
- for each text segment of the plurality of text segments:
- generating, using the ML model, a respective text summary based on the text segment, and
- adding the respective text summary to a plurality of text summaries;
- generating the summary based on the plurality of text summaries;
- and
- causing the summary to be output by way of a user interface on the client computing device.
A server computing device, comprising:
- at least one processor;
- and
- at least one memory storing instructions that, when executed by the at least one processor, cause the computing device to carry out steps that include:
- receiving a query from a client computing device, wherein the query comprises a request to generate a summary of text content included in the query;
- determining that a size of the text content exceeds an input limit associated with an ML model to be utilized to generate the summary;
- separating the text content into a plurality of text segments, wherein each text segment of the plurality of text segments is sized in accordance with the input limit;
- for each text segment of the plurality of text segments:
- generating, using the ML model, a respective text summary based on the text segment, and
- adding the respective text summary to a plurality of text summaries;
- generating the summary based on the plurality of text summaries;
- and
- causing the summary to be output by way of a user interface on the client computing device.
Dependencies are inferred from the claim text.