code-understanding

There are 14 repositories under code-understanding topic.

  • salesforce/CodeT5

    Home of CodeT5: Open Code LLMs for Code Understanding and Generation

    Language:Python2.7k40166395

  • salesforce/CodeTF

    CodeTF: One-stop Transformer Library for State-of-the-art Code LLM

    Language:Python1.4k213499

  • HugAILab/HugNLP

    CIKM2023 Best Demo Paper Award. HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊

    Language:Python37571245

  • wjn1996/HugNLP

    HugNLP is a unified and comprehensive NLP library based on HuggingFace Transformer. Please hugging for NLP now!😊 HugNLP will released to @HugAILab

    Language:Python2508013

  • wala/graph4code

    GraphGen4Code: a toolkit for creating code knowledge graphs based on WALA code analysis and extraction of documentation and forum content.

    Language:Jupyter Notebook208101831

  • FSoft-AI4Code/RepoPilot

    Repo-Level Coding Assistant that Can Understand Your Whole Codebase

    Language:Python98838

  • RepoAnalysis/RepoSnipy

    Neural search engine for discovering semantically similar Python repositories on GitHub

    Language:Python23106

  • CRJFisher/code-charter

    Visual summaries for code repositories

    Language:TypeScript12100

  • RepoAnalysis/RepoSim

    This repository contains experiments on comparing the similarity of Python repositories using ML models.

    Language:Jupyter Notebook3002

  • williamfzc/srctag

    Tag source files with real-world stories.

    Language:Python333

  • Jaso1024/Semantic-Code-Embeddings

    IEEE 2023 | SCALE: Semantic Code Analysis via Learned Embeddings

    Language:Python2200

  • RepoMining/RepoSim4Py

    A project for determining the similarity of python repositories based on embedding approach

    Language:Jupyter Notebook2002

  • GNOEYHEAT/CodeSim_cpp

    코드 유사성 판단 시즌2 AI 경진대회, DACON (2024.03.04 ~ 2024.04.01)

    Language:Python1200

  • QuantLet/Encode-the-Qode

    Towards Code Summarization for Scientific Domain Experts on Scarce Data (Code accompanying the research paper)

    Language:Jupyter Notebook1