README.md

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title: README
emoji: 👀
colorFrom: yellow
colorTo: purple
sdk: static
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This organization is dedicated to language models for code generation. In particular CodeParrot is a GPT-2 model trained to generate Python code.

Table of contents:

• Interactive blog: where we compare different code models and explain how they are trained and evaluated Code generation with 🤗




• Spaces: code generation with: CodeParrot (1.5B), InCoder (6B) and CodeGen (6B)



• Models: CodeParrot (1.5B) and CodeParrot-small (110M), each repo has different ongoing experiments in the branches.


• Datasets:
  • codeparrot-clean, dataset on which we trained and evaluated CodeParrot, the splits are available under codeparrot-clean-train and codeparrot-clean-valid.
  • A more filtered version of codeparrot-clean under codeparrot-train-more-filtering and codeparrot-train-more-filtering.
  • CodeParrot dataset after near deduplication since initially only exact match deduplication was performed, it's available under codeparrot-train-near-deduplication and codeparrot-train-near-deduplication.
  • GitHub-Code, a 1TB dataset of 32 programming languages with 60 from GitHub files.
  • GitHub-Jupyter, a 16.3GB dataset of Jupyter Notebooks from BigQuery GitHub.
  • APPS, a benchmark for code generation with 10000 problems.