This project does not have as purpose to be used to develop tokenizers. I just aim to develop this framework by myself to get a better understanding of how tokenizers work, by implementing in different ways, and comparing to performing ones, such as Tiktoken.
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Table of Contents
Backend | Frontend | |
---|---|---|
Server | ||
Libraries/Frameworks | ||
Tokenizers |
- Clone the repo
git clone git@github.com:art-test-stack/tokenizer.git
- Run the Python server
-
Create a virtual environment
For example I use virtualenv:
virtualenv -p python 3.10 venv
- Install pip packages
pip install -r requirements.txt
- Run the server
uvicorn main:app --reload --host 0.0.0.0 --port 8000
- Run the web app in another shell
-
Install npm, for some doc look at npm getting started
-
Run the app
npm run start
- [ ]
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Distributed under the MIT License. See LICENSE.txt
for more information.
Arthur Testard - testardarthur@gmail.com
Project Link: https://github.com/art-test-stack/tokenizer