pyre-code
A self-hosted ML coding practice platform. 68 problems from ReLU to flow matching — attention, training, RLHF, diffusion, and more. Instant feedback in the browser.
What is it?
What it is
Pyre Code is an open‑source, fully local platform that lets developers implement core components of modern AI systems—Transformers, vLLM, TRL, diffusion models, GNNs, and more—directly in Python. It provides 76 graded problems, instant feedback, reference solutions, progress tracking, and optional AI hints, all without requiring a GPU.
Why it exists
It was created to give people a hands‑on playground for learning AI internals, preparing for machine‑learning interviews, and deepening their understanding by writing code instead of just reading about it.
Who should use it
ML interview candidateshands-on learnersengineers wanting to implement AI internalsstudents studying deep learning
Who should avoid it
those who prefer video lectures onlycomplete beginners with no ML backgroundthose seeking high-level overviews without coding
How it works
A quick walkthrough in plain English
How pyre-code works
Step 1 of 3
You interact with it
Open pyre-code, send a request, or connect it to your stack.
Features
Advantages
- Open source (NOASSERTION)
- Active Python ecosystem
- Self-hosted deployment options
Disadvantages
- Requires operational ownership for self-hosted setups
- Community support varies by project maturity
Installation
compose
Open `http://localhost:3000`. Progress is persisted in a Docker volume. Run `docker compose down -v` to reset. ### AI Help (optional) To enable server-side AI hints, copy `web/.env.example` to `web/.env` and fill in:
FAQ
What is pyre-code?
pyre-code is an open-source project licensed under NOASSERTION.
What language is pyre-code built with?
Primary language: Python.
Is it free to use?
Yes. Licensed under NOASSERTION. Check the license for commercial use.
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