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Fine-tuning cuBERT embeddings for clustering source code by functionality

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Learning and Evaluating Source Code Embeddings using cuBERT

Getting Started

We provide a docker image for easy deployment of the container in order to get up and running quickly. However, if you would like to skip this step then you can head over directly to the src-folder and follow the instructions here.

Docker

Prerequisites

Build the docker image

docker build -t scc .

Start the container, exposing the GPUs and open a terminal prompt.

docker run -it --gpus all scc /bin/bash

The container is now up and running with all the necessary dependencies installed. Instructions for running the code are available here

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Fine-tuning cuBERT embeddings for clustering source code by functionality

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  • Python 99.5%
  • Dockerfile 0.5%