Register
Login
Resources
Docs Blog Datasets Glossary Case Studies Tutorials & Webinars
Product
Data Engine LLMs Platform Enterprise
Pricing Explore
Connect to our Discord channel
Integration:  git github
dc442194e5
data download from GCP
4 years ago
51f0529222
python call graph analysis code
2 years ago
fdb8415ce8
gemfile vulnerability
2 years ago
baa6915386
setup for code summarization
1 year ago
cb779f5b76
training cross encoders on code
1 year ago
aa42f940fb
Python repository imports
3 years ago
3 years ago
6bdd909614
moved some functions from notebooks to packagages
4 years ago
d07ffc7a6e
cleanup
2 years ago
7ca0a14e31
README, ploomber config refactor
2 years ago
dc442194e5
data download from GCP
4 years ago
baa6915386
setup for code summarization
1 year ago
daa81ccce2
refactoring preprocessing, tests
4 years ago
50a4b5910e
guild changes
4 years ago
baa6915386
setup for code summarization
1 year ago
6bdd909614
moved some functions from notebooks to packagages
4 years ago
2b060c04bd
updated requirements, gradio demo
2 years ago
77414a025b
pipeline for fetching import data
2 years ago
8f01f1bfc2
nbdev setup
3 years ago
Storage Buckets
Data Pipeline
Legend
DVC Managed File
Git Managed File
Metric
Stage File
External File

README.md

You have to be logged in to leave a comment. Sign In

github-search

Repository for "Searching Github Python repositories with machine learning" masters thesis

Jakub Bartczuk

Running this project

Prerequisites

Preprocessing steps were tested on a machine with 64GB RAM.

For training Graph Neural Networks CUDA GPU is required.

General remarks

The project uses nbdev to create Python files from Jupyter notebook. To "make" project run

nbdev_build_lib; pip install -e .

in the root directory.

We use ploomber for managing training and data preprocessing.

For example to create csv files with extracted READMEs run

ploomber build --partial make_readmes --skip-upstream --force

Relevant definitions can be found in pipeline.yaml and env.yaml

TODO Downloading data

TODO Model checkpoints

Training models

Ploomber step:

run_gnn_experiment

TODO Using models

Tip!

Press p or to see the previous file or, n or to see the next file

About

No description

Collaborators 1

Comments

Loading...