Patent ID: 11947935
Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 8:
9. A computer-implemented method, comprising:
accessing a pre-trained deep learning model trained to generate source code given a context, wherein the pre-trained deep learning model includes a plurality of model parameters, wherein the pre-trained deep learning model includes an input layer, an output layer, and a plurality of transformer blocks, wherein the input layer and the output layer are in a first execution environment, wherein the plurality of transformer blocks are in a second execution environment, wherein the first execution environment differs from the second execution environment;
receiving, from the input layer, a tuning dataset of a target source code generation task, wherein the tuning dataset including a plurality of input sequences, an input sequence of the plurality of input sequences including a prefix prepended to source code samples, wherein the prefix includes a plurality of trainable parameters distinct from the plurality of model parameters;
applying the tuning dataset to the plurality of transformer blocks in the second execution environment to create a custom model for the target source code generation task, wherein application of the tuning dataset optimizes the prefix to minimize a cost function without altering the plurality of model parameters; and
outputting the custom model to generate source code for the target source code generation task.