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`PyCoder` is a tool to generate python code out of a few given topics and a description. It uses GPT-2 language model as its engine. Pycoder poses writing Python code as a conditional-Causal Language Modelling(c-CLM). It has been trained on millions of lines of Python code written by all of us. At the current stage and state of training, it produces sensible code with few lines of description, but the scope of improvement for the model is limitless. Pycoder has been developed as a Command-Line tool (CLI), an API endpoint, as well as a python package (yet to be deployed to PyPI). This repository acts as a framework for anyone who either wants to try to build Pycoder from scratch or turn Pycoder into maybe a `CPPCoder` or `JSCoder` 😃. A blog post about the development of the project will be released soon. To use `Pycoder` as a CLI utility, clone the repository as normal, and install the package with: ```console foo@bar:❯ pip install pycoder ``` After this the package could be verified and accessed as either a native CLI tool or a python package with: ```console foo@bar:❯ python -m pycoder --version Or directly as: foo@bar:❯ pycoder --version ``` On installation the CLI can be used directly, such as: ```console foo@bar:❯ pycoder -t pytorch -t torch -d "a trainer class to train vision model" -ml 120 ``` The API endpoint is deployed using FastAPI. Once all the requirements have been installed for the project, the API can be accessed with: ```console foo@bar:❯ pycoder --endpoint PORT_NUMBER Or foo@bar:❯ pycoder -e PORT_NUMBER ```
## Tech Stack
Python PyTorch Transformers Docker FastAPI
## Tested Platforms
Linux Windows 10
## BibTeX If you want to cite the framework feel free to use this: ```bibtex @article{dutta2021pycoder, title={Pycoder}, author={Dutta, H}, journal={GitHub. Note: https://github.com/himanshu-dutta/pycoder}, year={2021} } ```
MIT License