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xingjian-bai/opal

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Can I trust it?

Worth a closer look before you use it.

  • Warnings Check

    Very new: it was created 2 days ago. Wait a little before installing it.

  • Stars from real accounts No data

    We haven't checked its stars for fakes yet.

  • Active OK

    Last change today.

  • Licence OK

    MIT: you can use it for free, also in a commercial product. Keep the licence notice.

Quick checks from public data. They help, but they are no guarantee.

What it is

A PyTorch optimizer wrapper that lets a coding agent (Claude Code) rewrite the optimizer's update rules, learning rates, schedules and related code while a model trains. Until the agent changes something, the wrapped run matches the plain run.

Who it's for

Machine learning engineers training PyTorch models who want to experiment with agent-driven optimizer changes during training

How to use it

Install

pip install "git+https://github.com/xingjian-bai/opal"

From its README. Check it there before running it.

Ask your AI to set it up

Paste this into Claude, ChatGPT or your coding assistant.

Help me install and set up xingjian-bai/opal in my project. Follow its README: https://github.com/xingjian-bai/opal. Explain each step and check it is safe before running anything.

Star curve

164From 52 to 164 stars between 21 Oct 2026 and 23 Oct 2026.

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