Gradient-free optimization of large language models
AssigneeSalesforce, Inc.
InventorsRomain Cosentino, Sarath Shekkizhar
Life of this patent
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Abstract
Gradient-free optimization of deep learning models it performed by iteratively improving the text prompt used to instruct the deep learning model to perform a given task. An initial prompt is obtained and used to generate an initial output by the model to be optimized. This output is evaluated by an evaluation model along with reference data, evaluation criteria, etc. The evaluation model's reasoning can be used to generate a new prompt that can be passed back to the deep learning model and used to generate a new model output. This process can continue iteratively until an end condition is met.
Claims20
A non-transitory machine-readable storage medium that provides instructions that, if executed by a processor, are configurable to cause the processor to perform operations comprising:
- obtaining, by a deep learning model, a text prompt describing a task to be performed by the deep learning model;
- generating an output by the deep learning model based at least on the text prompt;
- processing the output by an evaluation model to generate a model evaluation;
- generating a new prompt based at least on the model evaluation;
- and
- generating, by the deep learning model, an optimized output based at least on the new prompt.
A method comprising:
- obtaining, by a deep learning model, a text prompt describing a task to be performed by the deep learning model;
- generating an output by the deep learning model based at least on the text prompt;
- processing the output by an evaluation model to generate a model evaluation;
- generating a new prompt based at least on the model evaluation;
- and
- generating, by the deep learning model, an optimized output based at least on the new prompt.
An apparatus comprising:
- a processor;
- and
- a non-transitory machine-readable storage medium that provides instructions that, if executed by the processor, are configurable to cause the apparatus to perform operations comprising,
- obtaining, by a deep learning model, a text prompt describing a task to be performed by the deep learning model;
- generating an output by the deep learning model based at least on the text prompt;
- processing the output by an evaluation model to generate a model evaluation;
- generating a new prompt based at least on the model evaluation;
- and
- generating, by the deep learning model, an optimized output based at least on the new prompt.
Dependencies are inferred from the claim text.